Triple
T1459878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cal–Stanford Big Game |
E31485
|
entity |
| Predicate | reasonForInterruptions |
P7401
|
FINISHED |
| Object | world wars |
—
|
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: world wars | Statement: [Cal–Stanford Big Game, reasonForInterruptions, world wars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForInterruptions Context triple: [Cal–Stanford Big Game, reasonForInterruptions, world wars]
-
A.
interruptionDuration
Indicates the length of time for which an ongoing activity, process, or state is temporarily halted or disrupted.
-
B.
reasonForDiscontinuation
Indicates that one entity specifies the cause or justification for stopping, ending, or withdrawing another entity, process, or activity.
-
C.
suspensionReason
chosen
Indicates the reason or cause for which an entity has been suspended from a status, activity, or service.
-
D.
disruptsContinuityOf
Indicates that one entity interrupts, breaks, or otherwise prevents the ongoing, uninterrupted progression or sequence of another entity or process.
-
E.
hasHistoricalInterruptions
Indicates that the continuity of an event, process, or relationship has been broken by one or more distinct interruptions over time.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59d6dd88190b8ff3bda90aef7e2 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.