Triple
T22092329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parker |
E545941
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object |
Flashfire
Flashfire is a science fiction novel by David Sherman and Dan Cragg, known for its military themes and action-driven narrative.
|
E1519173
|
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: Flashfire | Statement: [Parker, basedOn, Flashfire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flashfire Context triple: [Parker, basedOn, Flashfire]
-
A.
Flash Point
Flash Point is a 2007 Hong Kong action film starring Donnie Yen, known for its intense mixed martial arts fight choreography and gritty police thriller storyline.
-
B.
Hang Fire
"Hang Fire" is a song by the Rolling Stones, featured on their 1981 album *Tattoo You*, known for its upbeat rock sound and satirical lyrics about economic hardship.
-
C.
Flame
Flame is a character from the Spyro video game series, known as a young orange dragon who appears as an alternate playable version of Spyro.
-
D.
Flames
The Flames are the athletic teams of Liberty University, most prominently known for their NCAA Division I football program.
-
E.
On Fire
On Fire is a nonfiction book by Naomi Klein that explores the climate crisis and advocates for transformative, justice-centered solutions such as a Green New Deal.
- 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: Flashfire Triple: [Parker, basedOn, Flashfire]
Generated description
Flashfire is a science fiction novel by David Sherman and Dan Cragg, known for its military themes and action-driven narrative.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Flashfire Target entity description: Flashfire is a science fiction novel by David Sherman and Dan Cragg, known for its military themes and action-driven narrative.
-
A.
Flash Point
Flash Point is a 2007 Hong Kong action film starring Donnie Yen, known for its intense mixed martial arts fight choreography and gritty police thriller storyline.
-
B.
Hang Fire
"Hang Fire" is a song by the Rolling Stones, featured on their 1981 album *Tattoo You*, known for its upbeat rock sound and satirical lyrics about economic hardship.
-
C.
Flame
Flame is a character from the Spyro video game series, known as a young orange dragon who appears as an alternate playable version of Spyro.
-
D.
Flames
The Flames are the athletic teams of Liberty University, most prominently known for their NCAA Division I football program.
-
E.
On Fire
On Fire is a nonfiction book by Naomi Klein that explores the climate crisis and advocates for transformative, justice-centered solutions such as a Green New Deal.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e6b1d881909bf0f4a52199354c |
completed | April 28, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a879b9130819089f8e2b7106f875b |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a891eb0708190a4575a01f45b98aa |
completed | May 18, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a89977c8c8190a5c87d1c2b68ed48 |
completed | May 18, 2026, 3:37 a.m. |
Created at: April 16, 2026, 8:29 p.m.