Triple
T33881931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1984 NCAA Division I men’s ice hockey championship |
E868514
|
entity |
| Predicate | championTitleCountForBowlingGreen |
P155255
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1984 NCAA Division I men’s ice hockey championship, championTitleCountForBowlingGreen, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championTitleCountForBowlingGreen Context triple: [1984 NCAA Division I men’s ice hockey championship, championTitleCountForBowlingGreen, 1]
-
A.
numberOfChampionTitles
chosen
Indicates the total count of championship titles that an entity has won.
-
B.
championsTitleWonBy
Indicates that a particular championship title is held or has been won by a specific entity.
-
C.
championSeriesWins
Indicates that one entity has won a championship series a specified number of times or in a specified context relative to another entity.
-
D.
championTitleCountOnCourt
Indicates the number of championship titles an entity has won on a particular court or playing surface.
-
E.
championPreviousTitleYear
Indicates the year in which the current champion previously held the same title.
- 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_69f34995b81c8190acdb45cea5a10eff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:48 a.m.