Triple
T38483034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2013 NCAA Division I Men's Basketball Championship Game |
E917835
|
entity |
| Predicate | MichiganScore |
P191166
|
FINISHED |
| Object | 76 |
—
|
LITERAL 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: 76 | Statement: [2013 NCAA Division I Men's Basketball Championship Game, MichiganScore, 76]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MichiganScore Context triple: [2013 NCAA Division I Men's Basketball Championship Game, MichiganScore, 76]
-
A.
VirginiaTechScore
Indicates the number of points scored by the Virginia Tech team in a particular game or event.
-
B.
Michigan StateScore
Indicates that a specified score is associated with Michigan State in a particular game or event.
-
C.
KansasScore
Indicates that a scoring event or point total is attributed to Kansas in a particular game, contest, or context.
-
D.
scores
Indicates that one entity achieves or is assigned a numerical result, rating, or points in relation to another entity, such as a test, game, or evaluation.
-
E.
usesScore
Indicates that one entity evaluates, measures, or makes decisions about another entity by applying a numerical or categorical score.
- F. None of above. chosen
Provenance (4 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcdaa2bfc08190beccabb0f1782d0d |
completed | May 7, 2026, 6:32 p.m. |
Created at: May 3, 2026, 4:31 p.m.