Triple
T19834505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nalchik Airport |
E476551
|
entity |
| Predicate | hasCode |
P9567
|
FINISHED |
| Object | URMN |
—
|
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: URMN | Statement: [Nalchik Airport, hasCode, URMN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: URMN Context triple: [Nalchik Airport, hasCode, URMN]
-
A.
URMN
chosen
URMN is the ICAO airport code assigned to Nalchik Airport in Russia.
-
B.
URM
URM is the commonly used Lithuanian abbreviation for the country’s Ministry of Foreign Affairs.
-
C.
URM
URM is the National Rail station code for Urmston railway station in Greater Manchester, England.
-
D.
URM
URM is the commonly used abbreviation for Union Rescue Mission, a prominent Christian homeless services organization based in Los Angeles.
-
E.
RMU
RMU is a public medical university located in Rawalpindi, Pakistan, known for training healthcare professionals and conducting medical research.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656d0e738819093000d3307962328 |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.