Triple
T24469854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Crimson Crew |
E617068
|
entity |
| Predicate | cityOfInstitutionAffiliation |
P263
|
FINISHED |
| Object | Denver |
—
|
NE NERFINISHED |
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: Denver | Statement: [The Crimson Crew, cityOfInstitutionAffiliation, Denver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityOfInstitutionAffiliation Context triple: [The Crimson Crew, cityOfInstitutionAffiliation, Denver]
-
A.
cityOfInstitution
chosen
Indicates the city in which an institution is located or based.
-
B.
universityLocatedIn
Indicates that a university is situated within or associated with a specific geographic location or administrative region.
-
C.
servesInstitution
Indicates that one entity provides services or functions in support of a particular institution.
-
D.
containsUniversityCity
Indicates that a given region or area includes within its boundaries a city that hosts a university.
-
E.
associatedInstitution
Indicates that an entity has a formal connection or affiliation with 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f299422cdc8190bc8d56243b7bc313 |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:20 a.m.