Triple
T5741292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | License to Wed |
E126619
|
entity |
| Predicate | storyBy |
P1955
|
FINISHED |
| Object | Kim Barker |
E543070
|
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: Kim Barker | Statement: [License to Wed, storyBy, Kim Barker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Barker Context triple: [License to Wed, storyBy, Kim Barker]
-
A.
Kim Barker
chosen
Kim Barker is an American screenwriter best known for writing the romantic comedy film "License to Wed."
-
B.
Kay Bawden
Kay Bawden is a social worker and one of the central adult characters in J.K. Rowling’s novel "The Casual Vacancy," whose professional and personal struggles highlight the book’s themes of class, responsibility, and community conflict.
-
C.
Nigel Starr
Nigel Starr is a music producer known for his work on the hip-hop track "Ego Trippin'."
-
D.
Martin Boddey
Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
-
E.
Michael Barker
Michael Barker is an American film executive and co-president of Sony Pictures Classics, known for distributing acclaimed independent and arthouse films.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0258382908190af8787feb1e5fbcd |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097f655e881909f6944e9a9d27e6c |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:48 p.m.