Triple
T7532175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frailty |
E178049
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Corey Sienega
Corey Sienega is a film producer best known for her work on genre and independent movies, including the psychological horror-thriller "Frailty."
|
E678662
|
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: Corey Sienega | Statement: [Frailty, producer, Corey Sienega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Corey Sienega Context triple: [Frailty, producer, Corey Sienega]
-
A.
Corey Gaines
Corey Gaines is an American basketball coach and former player best known for leading the WNBA’s Phoenix Mercury to a championship as head coach.
-
B.
Corey Britz
Corey Britz is an American bassist and musician best known for playing with the British rock band Bush.
-
C.
Corey Palent
Corey Palent is a television producer best known for serving as an executive producer of the daytime talk program "The Jennifer Hudson Show."
-
D.
Corey Hill
Corey Hill is a residential neighborhood in Brookline, Massachusetts, known for its steep hillside setting and views overlooking Boston.
-
E.
Corey Moosa
Corey Moosa is an American film producer best known for his work on independent features such as the financial thriller "Margin Call."
- 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: Corey Sienega Triple: [Frailty, producer, Corey Sienega]
Generated description
Corey Sienega is a film producer best known for her work on genre and independent movies, including the psychological horror-thriller "Frailty."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Corey Sienega Target entity description: Corey Sienega is a film producer best known for her work on genre and independent movies, including the psychological horror-thriller "Frailty."
-
A.
Corey Gaines
Corey Gaines is an American basketball coach and former player best known for leading the WNBA’s Phoenix Mercury to a championship as head coach.
-
B.
Corey Britz
Corey Britz is an American bassist and musician best known for playing with the British rock band Bush.
-
C.
Corey Palent
Corey Palent is a television producer best known for serving as an executive producer of the daytime talk program "The Jennifer Hudson Show."
-
D.
Corey Hill
Corey Hill is a residential neighborhood in Brookline, Massachusetts, known for its steep hillside setting and views overlooking Boston.
-
E.
Corey Moosa
Corey Moosa is an American film producer best known for his work on independent features such as the financial thriller "Margin Call."
- 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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f84753fc81908bee2013004ef5fb |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c87070d8a88190afde21f548d86292 |
completed | March 29, 2026, 12:21 a.m. |
| NEDg | Description generation | batch_69c8723391f48190b60ba8952c9ccca7 |
completed | March 29, 2026, 12:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c87401aaa48190b3e44298fcd3f37f |
completed | March 29, 2026, 12:36 a.m. |
Created at: March 27, 2026, 3:47 p.m.