Triple
T5486910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAN Airlines |
E123604
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | LA |
E174686
|
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: LA | Statement: [LAN Airlines, IATAcode, LA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LA Context triple: [LAN Airlines, IATAcode, LA]
-
A.
LA
chosen
LA is the IATA airline designator used by LATAM Airlines Group, a major South American airline conglomerate.
-
B.
LA
LA is the official two-letter U.S. Postal Service abbreviation for the state of Louisiana.
-
C.
LA
LA is the postcode area covering Lancaster and surrounding parts of north-west England, including parts of Cumbria and Lancashire.
-
D.
LA
LA is the standard abbreviation for the Lord Advocate, the chief legal officer of the Scottish Government and the Crown in Scotland.
-
E.
Los Angeles
Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd92639b3481908845c280d334117f |
completed | March 20, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf48aa12708190add69c5fd51d161d |
completed | March 22, 2026, 1:40 a.m. |
Created at: March 20, 2026, 2:10 p.m.