Triple
T20884277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Univ |
E514233
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Univ |
—
|
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: Univ | Statement: [Univ, shortName, Univ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Univ Context triple: [Univ, shortName, Univ]
-
A.
Univ
chosen
Univ is the informal abbreviation for University College, one of the constituent colleges of the University of Oxford.
-
B.
Universitet
Universitet is a Moscow Metro station serving the area around the Moscow State University campus on the Lenin Hills.
-
C.
Universitate
Universitate is a central Bucharest metro station located near the University of Bucharest and several major cultural and administrative landmarks.
-
D.
Universitas
Universitas is a Latin term commonly used to denote a university or community of scholars dedicated to higher learning and research.
-
E.
Universidad
Universidad is a Mexico City Metro station that serves as a major southern terminus and gateway to the National Autonomous University of Mexico (UNAM) campus.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67bd32c819097301e330e358c49 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:46 p.m.