Triple
T5980787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston University–Boston College men's ice hockey rivalry |
E133113
|
entity |
| Predicate | firstMeetingSport |
P67857
|
FINISHED |
| Object | men's ice hockey |
—
|
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: men's ice hockey | Statement: [Boston University–Boston College men's ice hockey rivalry, firstMeetingSport, men's ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMeetingSport Context triple: [Boston University–Boston College men's ice hockey rivalry, firstMeetingSport, men's ice hockey]
-
A.
firstMeets
Indicates that one entity encounters or comes into contact with another entity for the first time.
-
B.
firstMeetingSeason
Indicates the season of the year during which two entities first met.
-
C.
firstMeetingScore
Indicates the evaluated quality or outcome of an entity’s initial meeting or first interaction with another entity.
-
D.
firstMeetingPlace
Indicates the location where two or more entities met each other for the very first time.
-
E.
firstMetInLeague
Indicates that the two entities first met each other within the context of a particular league or league competition.
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:04 p.m.