Triple
T17747968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epitaph One |
E443035
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Victor
Victor is a character from the science fiction TV series "Dollhouse," appearing in the episode "Epitaph One."
|
E443026
|
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: Victor | Statement: [Epitaph One, featuresCharacter, Victor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victor Context triple: [Epitaph One, featuresCharacter, Victor]
-
A.
Victor
Victor was a prominent early 20th-century record label known for producing and distributing influential jazz and popular music recordings.
-
B.
Victor
Victor is a character in Gregory Benford’s science fiction novel "Timescape," which explores time communication and ecological catastrophe.
-
C.
Victor
Victor is the NATO reporting name for a class of Soviet nuclear-powered attack submarines developed during the Cold War.
-
D.
Victor
Victor is a supporting character in the romantic film "Letters to Juliet," known as Sophie’s work-obsessed fiancé whose priorities contrast with her search for true love.
-
E.
Victor
Victor is a trusted henchman and enforcer for drug kingpin Gustavo Fring in the television series Breaking Bad.
- 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: Victor Triple: [Epitaph One, featuresCharacter, Victor]
Generated description
Victor is a character from the science fiction TV series "Dollhouse," appearing in the episode "Epitaph One."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Victor Target entity description: Victor is a character from the science fiction TV series "Dollhouse," appearing in the episode "Epitaph One."
-
A.
Victor
chosen
Victor is a central character in the TV series "Dollhouse," known as one of the programmable "Actives" whose identity and memories are repeatedly altered for various missions.
-
B.
Victor
Victor is a character in Gregory Benford’s science fiction novel "Timescape," which explores time communication and ecological catastrophe.
-
C.
Victor
Victor is an alternate personality (alter ego) of the soap opera character Victoria "Viki" Lord from the series One Life to Live.
-
D.
Victor
Victor is a character in the play "One for the Road," serving as one of the figures through whom the story’s themes of power and oppression are explored.
-
E.
Victor
Victor is a trusted henchman and enforcer for drug kingpin Gustavo Fring in the television series Breaking Bad.
- F. None of above.
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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad46a50819089c87f74efe3c7ca |
completed | April 19, 2026, 6:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0242f965148190a7b76796546ab920 |
completed | May 11, 2026, 8:58 p.m. |
| NEDg | Description generation | batch_6a02455730948190b1151d24f260d768 |
completed | May 11, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0245c34d008190ae029000dc8e9cbc |
completed | May 11, 2026, 9:10 p.m. |
Created at: April 10, 2026, 10:10 a.m.