Triple
T18360996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiksi Airport |
E439913
|
entity |
| Predicate | hasICAOCode |
P419
|
FINISHED |
| Object | UEST |
—
|
NE NERFINISHED |
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: UEST | Statement: [Tiksi Airport, hasICAOCode, UEST]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UEST Context triple: [Tiksi Airport, hasICAOCode, UEST]
-
A.
UEST
chosen
UEST is the ICAO airport code for Tiksi Airport, a remote airfield serving the Arctic settlement of Tiksi in Russia’s Sakha Republic.
-
B.
QUE
QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
-
C.
QUE
QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
-
D.
QUEST
QUEST is a public engineering and science university in Nawabshah, Sindh, Pakistan, known for its programs in engineering, technology, and applied sciences.
-
E.
UES
UES is the main public university in El Salvador, recognized for its broad range of academic programs and significant role in the country’s higher education system.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e516db045c8190b20c209225a53b9a |
completed | April 19, 2026, 5:54 p.m. |
Created at: April 10, 2026, 10:37 a.m.