Triple
T14919989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notre Dame Fighting Irish |
E371482
|
entity |
| Predicate | varsityTeamsCountApproximate |
P6986
|
FINISHED |
| Object | 26 |
—
|
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: 26 | Statement: [Notre Dame Fighting Irish, varsityTeamsCountApproximate, 26]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: varsityTeamsCountApproximate Context triple: [Notre Dame Fighting Irish, varsityTeamsCountApproximate, 26]
-
A.
hasVarsityTeams
Indicates that an institution fields official varsity-level sports teams.
-
B.
governsNumberOfVarsityTeams
Indicates that one entity has authority over or control of how many varsity teams another entity has.
-
C.
numberOfTeamsInUnitedStates
Indicates the total count of teams that are located within or belong to the United States.
-
D.
typicalNumberOfTopDivisionTeams
Indicates the usual or standard number of teams that compete in the highest-level division of a league or competition.
-
E.
hasNumberOfTeams
chosen
Indicates the quantity of teams associated with or contained by a given entity.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded62f76bc81909ebc8899096cd1a0 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:33 a.m.