Triple
T31804689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity Blue and White |
E811839
|
entity |
| Predicate | teamNicknameType |
P48350
|
FINISHED |
| Object | color-based nickname |
—
|
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: color-based nickname | Statement: [Trinity Blue and White, teamNicknameType, color-based nickname]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamNicknameType Context triple: [Trinity Blue and White, teamNicknameType, color-based nickname]
-
A.
teamNickname
Indicates the commonly used informal or symbolic name by which a team is known.
-
B.
teamNicknamedAfter
Indicates that a team is commonly referred to by a nickname derived from or inspired by another entity.
-
C.
notableTeamNickname
Indicates that a team is commonly known by a particular nickname that is notable or widely recognized.
-
D.
teamNameType
chosen
Indicates the type or category associated with a team's name (e.g., formal name, short name, nickname).
-
E.
teamNicknameOperated
Indicates that a particular team was operated under, or associated with, a specific nickname.
- 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_69f348e70d188190b4637c5509f81274 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca3dedc81908b519d53d2909868 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:42 p.m.