Triple
T6403883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bound 2 |
E144127
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Eric Danchick
Eric Danchick is a film producer known for his work on the movie "Bound 2."
|
E632606
|
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: Eric Danchick | Statement: [Bound 2, producer, Eric Danchick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Danchick Context triple: [Bound 2, producer, Eric Danchick]
-
A.
Kevin Hageman
Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
-
B.
Bryan Devendorf
Bryan Devendorf is an American drummer best known as a founding member and rhythmic backbone of the indie rock band The National.
-
C.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
-
D.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
-
E.
Scott Duxbury
Scott Duxbury is a British football executive best known for his long-standing leadership role at Watford Football Club.
- 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: Eric Danchick Triple: [Bound 2, producer, Eric Danchick]
Generated description
Eric Danchick is a film producer known for his work on the movie "Bound 2."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eric Danchick Target entity description: Eric Danchick is a film producer known for his work on the movie "Bound 2."
-
A.
Kevin Hageman
Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
-
B.
Bryan Devendorf
Bryan Devendorf is an American drummer best known as a founding member and rhythmic backbone of the indie rock band The National.
-
C.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
-
D.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
-
E.
Scott Duxbury
Scott Duxbury is a British football executive best known for his long-standing leadership role at Watford Football Club.
- 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_69c008dc56fc81908d43ffcc11d73bdd |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c068b0950c819091169aa1a3be0e88 |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7616755d48190b285ff66ccd8bf3a |
completed | March 28, 2026, 5:04 a.m. |
| NEDg | Description generation | batch_69c76228a3848190b939cfa55e15a5ca |
completed | March 28, 2026, 5:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76292355881908560d36f7f7e9141 |
completed | March 28, 2026, 5:09 a.m. |
Created at: March 22, 2026, 4:35 p.m.