Triple
T8708815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amos Kendall |
E206720
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kendall |
E230734
|
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: Kendall | Statement: [Amos Kendall, familyName, Kendall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kendall Context triple: [Amos Kendall, familyName, Kendall]
-
A.
Kendall
chosen
Kendall is a unisex given name of English origin commonly used in the United States and other English-speaking countries.
-
B.
Kendall
Kendall is a neighborhood in Cambridge, Massachusetts, known for its proximity to MIT and its concentration of technology companies and research institutions.
-
C.
Kendall Taylor
Kendall Taylor is an American businessman best known as the husband of singer and "American Idol" winner Fantasia Barrino.
-
D.
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.
-
E.
Kendall Duncan
Kendall Duncan is a character appearing in the fantasy-comedy film "Bedtime Stories."
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58ffa6a481908866b6239d1d9b92 |
completed | March 31, 2026, 11:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28b78e90819098ab1d4877ab88fe |
completed | April 3, 2026, 2:40 a.m. |
Created at: March 30, 2026, 6:35 p.m.