Triple
T27627460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Classic |
E696244
|
entity |
| Predicate | isNeutralRelativeTo |
P162774
|
FINISHED |
| Object | Texas A&M Aggies football team |
—
|
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: Texas A&M Aggies football team | Statement: [Southwest Classic, isNeutralRelativeTo, Texas A&M Aggies football team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNeutralRelativeTo Context triple: [Southwest Classic, isNeutralRelativeTo, Texas A&M Aggies football team]
-
A.
isNeutralRelativeTo
chosen
Indicates that one entity maintains a neutral, non-favoring stance or position with respect to another entity.
-
B.
isNeutral
Indicates that an entity maintains a balanced, unbiased, or non-aligned stance with respect to other entities, options, or conflicting sides.
-
C.
isNeutralUnder
Indicates that one entity does not affect, alter, or interact with another in a way that changes its state, value, or behavior.
-
D.
isNeutralOn
Indicates a stance of neither support nor opposition toward a subject, remaining impartial or undecided.
-
E.
isNeutralAbout
Indicates that one entity has no strong positive or negative opinion, preference, or stance toward another entity or subject.
- F. None of above.
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_69ef59092c8881908114ad184248cc46 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 2:18 p.m.