Triple
T20517613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Woodcock |
E503720
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Michael Carnes
Michael Carnes is a screenwriter best known for co-writing the comedy film "Mr. Woodcock."
|
E1437960
|
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: Michael Carnes | Statement: [Mr. Woodcock, screenwriter, Michael Carnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Carnes Context triple: [Mr. Woodcock, screenwriter, Michael Carnes]
-
A.
John Carnes
John Carnes was an American industrialist best known for co-founding the Lima Locomotive Works, a major manufacturer of steam locomotives in the United States.
-
B.
Dan Rydell
Dan Rydell is a charismatic, quick-witted sports anchor and one of the central protagonists on the television series "Sports Night."
-
C.
Philip Tyler Keaggy
Philip Tyler Keaggy is an American guitarist, singer, and songwriter renowned in contemporary Christian music for his virtuosic playing and prolific recording career.
-
D.
Mike Reno
Mike Reno is a Canadian rock singer best known as the lead vocalist of the band Loverboy and for his prominent contributions to 1980s rock and soundtrack hits.
-
E.
Michael Merrill
Michael Merrill is the son of legendary American actress Bette Davis, known for his later role in managing her estate and legacy.
- 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: Michael Carnes Triple: [Mr. Woodcock, screenwriter, Michael Carnes]
Generated description
Michael Carnes is a screenwriter best known for co-writing the comedy film "Mr. Woodcock."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Carnes Target entity description: Michael Carnes is a screenwriter best known for co-writing the comedy film "Mr. Woodcock."
-
A.
John Carnes
John Carnes was an American industrialist best known for co-founding the Lima Locomotive Works, a major manufacturer of steam locomotives in the United States.
-
B.
Dan Rydell
Dan Rydell is a charismatic, quick-witted sports anchor and one of the central protagonists on the television series "Sports Night."
-
C.
Philip Tyler Keaggy
Philip Tyler Keaggy is an American guitarist, singer, and songwriter renowned in contemporary Christian music for his virtuosic playing and prolific recording career.
-
D.
Mike Reno
Mike Reno is a Canadian rock singer best known as the lead vocalist of the band Loverboy and for his prominent contributions to 1980s rock and soundtrack hits.
-
E.
Michael Merrill
Michael Merrill is the son of legendary American actress Bette Davis, known for his later role in managing her estate and legacy.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f42db688190a3ccfba5601e8bf3 |
completed | April 20, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08acd15e888190a1e3f9689d202b88 |
completed | May 16, 2026, 5:43 p.m. |
| NEDg | Description generation | batch_6a08ad7f0cac81908bd2aa0cafe95b15 |
completed | May 16, 2026, 5:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08adeae6d881909b19929e0e5aa1c9 |
completed | May 16, 2026, 5:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.