Triple
T571464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvard Crimson women’s rowing |
E13671
|
entity |
| Predicate | teamName |
P7598
|
FINISHED |
| Object | Crimson |
E308
|
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: Crimson | Statement: [Harvard Crimson women’s rowing, teamName, Crimson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crimson Context triple: [Harvard Crimson women’s rowing, teamName, Crimson]
-
A.
Crimson
chosen
Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
-
B.
Red
Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
-
C.
Reddish
Reddish is a suburban area and former industrial village in the Metropolitan Borough of Stockport, Greater Manchester, England.
-
D.
Black-and-Red
Black-and-Red is the widely used nickname for Major League Soccer club D.C. United, referencing the team’s traditional colors and identity.
-
E.
Orange
Orange is a regional city in the Central Tablelands of New South Wales, Australia, known for its cool-climate wines, agriculture, and growing tourism industry.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b483ac08190b3be152a7cf42011 |
completed | March 1, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4fc8475d881909e80d60fbb50c271 |
completed | March 2, 2026, 2:57 a.m. |
Created at: March 1, 2026, 7:33 p.m.