Triple
T13027658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strength of a Woman |
E326348
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Troy Taylor |
E229357
|
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: Troy Taylor | Statement: [Strength of a Woman, producer, Troy Taylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troy Taylor Context triple: [Strength of a Woman, producer, Troy Taylor]
-
A.
Troy Taylor
chosen
Troy Taylor is an American R&B record producer and songwriter known for his work with artists such as Trey Songz and Whitney Houston.
-
B.
Troy Ryan
Troy Ryan is a Canadian ice hockey coach best known for leading the Canadian women’s national team to multiple international successes, including Olympic and World Championship gold medals.
-
C.
Troy Verges
Troy Verges is an American songwriter and record producer known for his work in contemporary country and pop music.
-
D.
Troy Miller
Troy Miller is an American film and television director and producer known for his work in comedy specials, series, and feature films.
-
E.
Troy Barlow
Troy Barlow is a U.S. Army reservist and one of the central soldiers in the 1999 war film "Three Kings," portrayed by Mark Wahlberg.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efc07488190a15f3e41ea2db45c |
completed | April 10, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ead058ac819091b13ddd25067869 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 8:53 p.m.