Triple
T7312148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China Airlines |
E168116
|
entity |
| Predicate | IATA airline designator |
P12360
|
FINISHED |
| Object | CI |
E168115
|
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: CI | Statement: [China Airlines, IATA airline designator, CI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CI Context triple: [China Airlines, IATA airline designator, CI]
-
A.
CI
chosen
CI is the IATA airline designator for China Airlines, the flag carrier of Taiwan.
-
B.
CI
CI is the commonly used abbreviation for California State University Channel Islands, a public university in Camarillo, California.
-
C.
CI
CI is the common abbreviation for the Coppa Italia, Italy’s premier national football cup competition.
-
D.
CI
CI is the station code used to identify Central Islip station on the Long Island Rail Road.
-
E.
IC
IC is a common abbreviation for Iowa City, a university-centered community best known as the home of the University of Iowa and its renowned Writers' Workshop.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ec00fef081909cb9768a70cabd80 |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eeeedea88190a17cf6b83abc10d8 |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 3:02 p.m.