Triple
T17309461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reese Stadium |
E420253
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | Yale University |
—
|
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: Yale University | Statement: [Reese Stadium, ownedBy, Yale University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yale University Context triple: [Reese Stadium, ownedBy, Yale University]
-
A.
Yale University
chosen
Yale University is an Ivy League research university in New Haven, Connecticut, renowned for its prestigious academic programs, historic campus, and influential alumni.
-
B.
Yale
Yale is a small unincorporated community located in Kansas, United States.
-
C.
Yale
Yale is a historic town in British Columbia, Canada, that served as a key hub during the Cariboo Gold Rush and the construction of the Canadian Pacific Railway.
-
D.
Yale
Yale is a widely used romanization system for Cantonese Chinese that represents Cantonese sounds with the Latin alphabet.
-
E.
Yale
"Yale" is a popular track by American rapper Ken Carson, known for its aggressive delivery and distorted, hypertrap production style.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439970cf08190bc9e49ba830da0d9 |
completed | April 19, 2026, 2:10 a.m. |
Created at: April 10, 2026, 5:43 a.m.