Triple
T3735090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yale Bulldogs swimming and diving |
E79161
|
entity |
| Predicate | color |
P60
|
FINISHED |
| Object | Yale Blue |
E1533
|
NE 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: Yale Blue | Statement: [Yale Bulldogs swimming and diving, color, Yale Blue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yale Blue Context triple: [Yale Bulldogs swimming and diving, color, Yale Blue]
-
A.
Yale Blue
chosen
Yale Blue is a deep, rich shade of blue traditionally associated with academic institutions and collegiate branding.
-
B.
Berkeley Blue
Berkeley Blue is a deep navy shade that serves as one of the primary official colors representing the University of California, Berkeley.
-
C.
Columbia blue
Columbia blue is a light, powdery shade of blue traditionally associated with and popularized by Columbia University.
-
D.
Duke blue
Duke blue is the distinctive deep royal blue shade associated with Duke University’s branding and athletic teams.
-
E.
Yonsei blue
Yonsei blue is the distinctive deep blue color traditionally associated with and prominently used in the identity and branding of Yonsei University.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb39dc0881909cd74ff25d8c43a9 |
completed | March 8, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db1be1388190a887d9eca0f4f9b3 |
completed | March 14, 2026, 3:50 a.m. |
Created at: March 8, 2026, 3:34 p.m.