Triple
T6358975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beslan Airport |
E143061
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
URMO
URMO is the ICAO airport code for Beslan Airport, which serves the city of Vladikavkaz in North Ossetia–Alania, Russia.
|
E587519
|
NE FINISHED |
How this triple was built (4 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: URMO | Statement: [Beslan Airport, ICAOcode, URMO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: URMO Context triple: [Beslan Airport, ICAOcode, URMO]
-
A.
URU
URU is the FIFA country code used to represent the Uruguay national football team in international competitions and rankings.
-
B.
Urke
Urke is a small village in Norway situated along the scenic Hjørundfjord, known for its dramatic mountain surroundings and fjord landscapes.
-
C.
URM
URM is the National Rail station code for Urmston railway station in Greater Manchester, England.
-
D.
Urambo
Urambo is a town and district headquarters in western Tanzania known historically for tobacco production and its location within the Tabora Region.
-
E.
Rumuokurusi
Rumuokurusi is a prominent urban community in Obio-Akpor, Rivers State, Nigeria, known for its commercial activity and strategic location within the Port Harcourt metropolitan area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: URMO Triple: [Beslan Airport, ICAOcode, URMO]
Generated description
URMO is the ICAO airport code for Beslan Airport, which serves the city of Vladikavkaz in North Ossetia–Alania, Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: URMO Target entity description: URMO is the ICAO airport code for Beslan Airport, which serves the city of Vladikavkaz in North Ossetia–Alania, Russia.
-
A.
URU
URU is the FIFA country code used to represent the Uruguay national football team in international competitions and rankings.
-
B.
Urke
Urke is a small village in Norway situated along the scenic Hjørundfjord, known for its dramatic mountain surroundings and fjord landscapes.
-
C.
URM
URM is the National Rail station code for Urmston railway station in Greater Manchester, England.
-
D.
Urambo
Urambo is a town and district headquarters in western Tanzania known historically for tobacco production and its location within the Tabora Region.
-
E.
Rumuokurusi
Rumuokurusi is a prominent urban community in Obio-Akpor, Rivers State, Nigeria, known for its commercial activity and strategic location within the Port Harcourt metropolitan area.
- F. None of above. chosen
Provenance (5 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f72f8481908f9df0c0cdf22a52 |
completed | March 22, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62d66a8a08190b52bb8302787dac5 |
completed | March 27, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_69c62e430ac08190bacf74f6086b2ac5 |
completed | March 27, 2026, 7:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c62f03ea408190a0959b8f2aa746c1 |
completed | March 27, 2026, 7:17 a.m. |
Created at: March 22, 2026, 4:32 p.m.