Triple
T10493178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Woman's Devotion |
E247468
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Robert Hill |
E500467
|
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: Robert Hill | Statement: [A Woman's Devotion, screenwriter, Robert Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Hill Context triple: [A Woman's Devotion, screenwriter, Robert Hill]
-
A.
Robert Hill
chosen
Robert Hill was a screenwriter known for his work on the film "The Big Operator" and other mid-20th-century American movies.
-
B.
David Wolstencroft
David Wolstencroft is a British television writer and producer best known for his work in the spy thriller genre.
-
C.
Edward Troup
Edward Troup is a British tax lawyer and civil servant best known for serving as Executive Chair of HM Revenue and Customs (HMRC).
-
D.
George Barr
George Barr is a science fiction and fantasy fan artist renowned for his distinctive illustrative work, which earned him recognition such as the Hugo Award for Best Fan Artist.
-
E.
George Barr
George Barr was a prominent Major League Baseball umpire active in the mid-20th century, known for officiating numerous significant games and for helping to professionalize umpire training.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097ecbec8190807c4fcc85662026 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dcaeb6088190829b6c26eb1de7d5 |
completed | April 10, 2026, 11:19 a.m. |
Created at: April 6, 2026, 12:24 p.m.