Triple
T659167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Major League Soccer regular season |
E11715
|
entity |
| Predicate | winPoints |
P7114
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Major League Soccer regular season, winPoints, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winPoints Context triple: [Major League Soccer regular season, winPoints, 3]
-
A.
winnerPoints
chosen
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
B.
winnerCount
Indicates the number of entities that are designated as winners in a given context or event.
-
C.
winnerThrows
Indicates that the entity identified as the winner performs or executes a throw action toward or involving another entity.
-
D.
wonFor
Indicates that one entity received an award, prize, or recognition specifically on behalf of or representing another entity.
-
E.
winnerReceives
Indicates that the entity identified as the winner is granted or awarded the specified item, benefit, or outcome as a result of winning.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d1406ec8190abf546549264c85d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.