Triple
T1458353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Airlines |
E31449
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | CAL |
E168116
|
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: [China Airlines, abbreviation, CAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAL Context triple: [China Airlines, abbreviation, CAL]
-
A.
CAL
chosen
CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
-
B.
CA
CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
-
C.
CO
CO is the Italian vehicle registration code for the Province of Como in the Lombardy region.
-
D.
CO
CO is the two-letter ISO 3166-1 alpha-2 country code assigned to Colombia for international identification and standardization purposes.
-
E.
SA
The SA (Sturmabteilung) was the Nazi Party’s paramilitary organization known for its role in Adolf Hitler’s rise to power through intimidation, street violence, and mass rallies in early 20th-century Germany.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59a462881908e84b27846a6bc04 |
completed | March 1, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15a299ac81908f37085a107c8e9f |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 8 p.m.