Triple
T594004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crosstown Classic |
E17337
|
entity |
| Predicate | competitiveContext |
P16079
|
FINISHED |
| Object | regular season |
—
|
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: regular season | Statement: [Crosstown Classic, competitiveContext, regular season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competitiveContext Context triple: [Crosstown Classic, competitiveContext, regular season]
-
A.
competition
Indicates a relationship where two or more entities strive against each other to achieve a superior outcome, advantage, or reward.
-
B.
competesWith
Indicates that two entities are in rivalry or opposition, each striving to outperform or gain advantage over the other in the same domain or objective.
-
C.
globalCompetition
Indicates a competitive relationship or rivalry that occurs between entities operating across multiple countries or on a worldwide scale.
-
D.
primaryCompetition
Indicates that one entity is the main or most significant competitor of another within a given market, domain, or context.
-
E.
competitionSurface
Indicates the type of surface or medium on which a competition or contest takes place.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd15c5881909b59ed4c88687e7b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cd7d3c8190af008acf34a2293b |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985ada988190aaea628a9b55bca4 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.