Triple
T22469674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Pevney |
E555460
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object |
The Deadly Years (Star Trek episode)
"The Deadly Years" is a first-season Star Trek: The Original Series episode in which the Enterprise crew is stricken with a rapid aging disease that threatens their lives and command of the ship.
|
E1539302
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: The Deadly Years (Star Trek episode) | Statement: [Joseph Pevney, directed, The Deadly Years (Star Trek episode)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Deadly Years (Star Trek episode) Context triple: [Joseph Pevney, directed, The Deadly Years (Star Trek episode)]
-
A.
The Doomsday Machine (TOS episode)
"The Doomsday Machine" is a highly acclaimed original Star Trek episode in which the Enterprise confronts a planet-destroying automated weapon and a traumatized Starfleet commodore obsessed with stopping it.
-
B.
Star Trek: The Next Generation – Skin of Evil
"Star Trek: The Next Generation – Skin of Evil" is a first-season episode of the science fiction television series Star Trek: The Next Generation, best known for the shocking death of the character Tasha Yar.
-
C.
Star Trek: The Entropy Effect
Star Trek: The Entropy Effect is a science fiction novel by Vonda N. McIntyre set in the Star Trek universe, known for its time-travel plot centered on Captain Kirk and Spock.
-
D.
Star Trek: Amok Time
Star Trek: Amok Time is a classic 1967 episode of the original Star Trek series, best known for exploring Vulcan culture and Spock’s mating drive through the iconic ritual combat on Vulcan.
-
E.
Star Trek: Voyager episode "Phage"
"Phage" is a first-season episode of Star Trek: Voyager that introduces the organ-harvesting alien race known as the Vidiians and explores the ethical dilemmas surrounding their survival.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Deadly Years (Star Trek episode) Triple: [Joseph Pevney, directed, The Deadly Years (Star Trek episode)]
Generated description
"The Deadly Years" is a first-season Star Trek: The Original Series episode in which the Enterprise crew is stricken with a rapid aging disease that threatens their lives and command of the ship.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Deadly Years (Star Trek episode) Target entity description: "The Deadly Years" is a first-season Star Trek: The Original Series episode in which the Enterprise crew is stricken with a rapid aging disease that threatens their lives and command of the ship.
-
A.
The Doomsday Machine (TOS episode)
"The Doomsday Machine" is a highly acclaimed original Star Trek episode in which the Enterprise confronts a planet-destroying automated weapon and a traumatized Starfleet commodore obsessed with stopping it.
-
B.
Star Trek: The Next Generation – Skin of Evil
"Star Trek: The Next Generation – Skin of Evil" is a first-season episode of the science fiction television series Star Trek: The Next Generation, best known for the shocking death of the character Tasha Yar.
-
C.
Star Trek: The Entropy Effect
Star Trek: The Entropy Effect is a science fiction novel by Vonda N. McIntyre set in the Star Trek universe, known for its time-travel plot centered on Captain Kirk and Spock.
-
D.
Star Trek: Amok Time
Star Trek: Amok Time is a classic 1967 episode of the original Star Trek series, best known for exploring Vulcan culture and Spock’s mating drive through the iconic ritual combat on Vulcan.
-
E.
Star Trek: Voyager episode "Phage"
"Phage" is a first-season episode of Star Trek: Voyager that introduces the organ-harvesting alien race known as the Vidiians and explores the ethical dilemmas surrounding their survival.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15bdeae9c8190a5b66e540484db37 |
completed | April 29, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b12568a7081908ef22da422fa90ca |
completed | May 18, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_6a0b14b7acac819090bfd6144df84be6 |
completed | May 18, 2026, 1:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b154f7e0c8190b0ca64d582982d62 |
completed | May 18, 2026, 1:34 p.m. |
Created at: April 16, 2026, 8:48 p.m.