Triple
T11223878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Golden Bears |
E265644
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Cal |
E310291
|
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: Cal | Statement: [California Golden Bears, shortName, Cal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cal Context triple: [California Golden Bears, shortName, Cal]
-
A.
Cal
chosen
Cal is the commonly used short name for the University of California, Berkeley and its associated athletic programs.
-
B.
Cal
Cal is the nickname and given name of Cal McNair, the American businessman and principal owner of the NFL’s Houston Texans.
-
C.
CAL
CAL is the station code for California station on the Green Line transit system.
-
D.
CAL
CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
-
E.
CAL
CAL was the stock ticker symbol for Continental Airlines, a major U.S. airline that later merged with United Airlines.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ec8fb08190b27144ab65f85957 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4978389848190ac5a8b985bbea15f |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:30 p.m.