Triple
T10412465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air China |
E245425
|
entity |
| Predicate | ICAOCode |
P419
|
FINISHED |
| Object | CCA |
E245423
|
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: CCA | Statement: [Air China, ICAOCode, CCA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CCA Context triple: [Air China, ICAOCode, CCA]
-
A.
CCA
chosen
CCA is the ICAO airline designator used to identify Air China in international aviation operations.
-
B.
CCA
CCA is the highest state court in Texas for criminal cases, serving as the court of last resort for all criminal matters in the state.
-
C.
CCA
CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
-
D.
CCA
CCA is an independent, not-for-profit organization in Canada that conducts expert assessments to inform public policy and decision-making on scientific and scholarly issues.
-
E.
CAC
The Central American Cup (CAC) is a regional football tournament featuring national teams from Central America competing for the championship title.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea0e17f081908fb16425f65e5808 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e9084fc81909e1d46a111a1ef2b |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:10 p.m.