Triple
T1440741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lobos |
E31063
|
entity |
| Predicate | notableCoach |
P550
|
FINISHED |
| Object | Craig Neal |
E38787
|
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: Craig Neal | Statement: [Lobos, notableCoach, Craig Neal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Neal Context triple: [Lobos, notableCoach, Craig Neal]
-
A.
Craig Neal
chosen
Craig Neal is an American basketball coach and former player best known for serving as head coach of the University of New Mexico Lobos men's basketball team.
-
B.
Tony Gayton
Tony Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
-
C.
Curtis Stigers
Curtis Stigers is an American jazz and soul-influenced singer, saxophonist, and songwriter known for his early 1990s pop hits and later critically acclaimed jazz recordings.
-
D.
Dave Moutrey
Dave Moutrey is a British arts leader and cultural executive best known for directing and developing Manchester’s HOME arts centre.
-
E.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5307e988190b392f1f1d1ac10f0 |
completed | March 1, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2328670c819087a2d8b047b67ee8 |
completed | March 8, 2026, 7:20 a.m. |
Created at: March 1, 2026, 8 p.m.