Triple
T18233465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kendall Taylor |
E436604
|
entity |
| Predicate | publiclyKnownAs |
P39
|
FINISHED |
| Object | Kendall Taylor |
—
|
NE NERFINISHED |
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: Kendall Taylor | Statement: [Kendall Taylor, publiclyKnownAs, Kendall Taylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kendall Taylor Context triple: [Kendall Taylor, publiclyKnownAs, Kendall Taylor]
-
A.
Kendall Taylor
chosen
Kendall Taylor is an American businessman best known as the husband of singer and "American Idol" winner Fantasia Barrino.
-
B.
Kendall Duncan
Kendall Duncan is a character appearing in the fantasy-comedy film "Bedtime Stories."
-
C.
Kendall Nesbitt
Kendall Nesbitt is a fictional character from the musical "Lady in the Dark," typically portrayed as a sophisticated romantic interest entangled in the protagonist's emotional and psychological journey.
-
D.
Kendall
Kendall is a fictional character portrayed by American actor Terry O'Quinn, best known for his roles in television dramas and thrillers.
-
E.
Kendall
Kendall is a neighborhood in Cambridge, Massachusetts, known for its proximity to MIT and its concentration of technology companies and research institutions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b512a88190aa493b0793ab28b3 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 10, 2026, 10:33 a.m.