Triple
T2075824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA women’s ice hockey tournament |
E44920
|
entity |
| Predicate | numberOfTeamsAtInception |
P3770
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [NCAA women’s ice hockey tournament, numberOfTeamsAtInception, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTeamsAtInception Context triple: [NCAA women’s ice hockey tournament, numberOfTeamsAtInception, 4]
-
A.
foundedWithNumberOfTeams
chosen
Indicates the number of teams involved at the time an organization, league, or competition was founded.
-
B.
team2Established
Indicates that a second team (team2) has been formally created or founded at a specific point in time.
-
C.
team1Established
Indicates that the first team in a given context has been founded or formally established.
-
D.
formerNumberOfTeams
Indicates the number of teams that an entity previously had before a change or reorganization.
-
E.
numberOfTeamsVariesByYear
Indicates that the number of teams involved changes depending on the specific year.
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba127dcc81909c2365d455eeb746 |
completed | March 7, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69abb7b0edac8190a58eabee55f73deb |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:41 p.m.