Triple
T6249583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bride Wars |
E140012
|
entity |
| Predicate | storyBy |
P1955
|
FINISHED |
| Object | Greg DePaul |
E583954
|
NE FINISHED |
How this triple was built (2 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: Greg DePaul | Statement: [Bride Wars, storyBy, Greg DePaul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg DePaul Context triple: [Bride Wars, storyBy, Greg DePaul]
-
A.
Greg DePaul
chosen
Greg DePaul is an American screenwriter and playwright best known for co-writing the romantic comedy film "Bride Wars."
-
B.
Marcus T. Paulk
Marcus T. Paulk is an American actor and rapper best known for his role as Myles Mitchell on the television sitcom "Moesha."
-
C.
Bill DeRonde
Bill DeRonde is a film editor best known for his work on the cult action film "The Boondock Saints."
-
D.
Darren Lemke
Darren Lemke is an American screenwriter and film producer known for working on fantasy and adventure films such as Jack the Giant Slayer and the Goosebumps movie adaptation.
-
E.
Michael Nolin
Michael Nolin is an American film producer best known for his work on the acclaimed music drama "Mr. Holland's Opus."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633c5f2081909b0246e061f8a7d9 |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c638568068819097811baeb8bf3ab3 |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:24 p.m.