Triple
T2299501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston University Terriers women’s lacrosse team |
E51695
|
entity |
| Predicate | playsForInstitutionType |
P29027
|
FINISHED |
| Object | private research university |
—
|
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: private research university | Statement: [Boston University Terriers women’s lacrosse team, playsForInstitutionType, private research university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsForInstitutionType Context triple: [Boston University Terriers women’s lacrosse team, playsForInstitutionType, private research university]
-
A.
playedCollegeTeam
Indicates that an athlete was a member of and competed for a particular college sports team.
-
B.
associatedInstitutionType
chosen
Indicates the type or category of institution with which an entity is associated.
-
C.
playedCollegeSport
Indicates that the subject participated in an organized college-level sport for the object institution.
-
D.
associatedInstitutionNickname
Indicates that an institution is commonly known or referred to by a particular nickname.
-
E.
servesInstitution
Indicates that one entity provides services or functions in support of a particular institution.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcbabf01081908db3b42bc7c60444 |
completed | March 7, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_69abc58ad33c8190b8d68af41b6f5e07 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.