Triple
T10039934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maryland State College football team |
E205267
|
entity |
| Predicate | colorAssociatedInstitution |
P92072
|
FINISHED |
| Object | maroon |
—
|
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: maroon | Statement: [Maryland State College football team, colorAssociatedInstitution, maroon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorAssociatedInstitution Context triple: [Maryland State College football team, colorAssociatedInstitution, maroon]
-
A.
associatedInstitutionNickname
Indicates that an institution is commonly known or referred to by a particular nickname.
-
B.
recognizedAsInstitutionBy
Indicates that an entity is acknowledged or accepted as an institution by a specified recognizing party.
-
C.
associatedInstitutionType
Indicates the type or category of institution with which an entity is associated.
-
D.
associatedInstitution
Indicates that an entity has a formal connection or affiliation with a particular institution.
-
E.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
- F. None of above. chosen
Provenance (4 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcee186708190bc9fecd637b4f7e6 |
completed | April 2, 2026, 2:05 a.m. |
| PD | Predicate disambiguation | batch_69cd4b8638508190b22acc65500ec7d6 |
completed | April 1, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69cd4fed19d481909d2c7ff1114664b6 |
completed | April 1, 2026, 5:03 p.m. |
Created at: March 30, 2026, 8:55 p.m.