Triple
T12877094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CalSTA |
E307996
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | CalSTA |
E307996
|
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: CalSTA | Statement: [CalSTA, abbreviation, CalSTA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CalSTA Context triple: [CalSTA, abbreviation, CalSTA]
-
A.
CalSTA
chosen
CalSTA is the California State Transportation Agency, a state-level cabinet agency responsible for overseeing and coordinating California’s transportation departments and policies.
-
B.
CSTACAA
CSTACAA is the French acronym for the Conseil supérieur des tribunaux administratifs et des cours administratives d’appel, a national body involved in overseeing and advising on the functioning and organization of France’s administrative courts and courts of administrative appeal.
-
C.
CAL
CAL is the station code for California station on the Green Line transit system.
-
D.
CAL
CAL is the commonly used abbreviation for the College of Arts and Letters, an academic division typically focused on humanities and liberal arts disciplines.
-
E.
CAL
CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fa8474819086a8af3c90f3ca84 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb83bac8190838f7537b806317c |
completed | May 3, 2026, 12:50 a.m. |
Created at: April 9, 2026, 5:38 p.m.