Triple
T13047555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakhon Ratchasima air base |
E327362
|
entity |
| Predicate | hasICAOCode |
P419
|
FINISHED |
| Object |
VTUQ
VTUQ is the ICAO airport code assigned to Nakhon Ratchasima Air Base in Thailand.
|
E1018024
|
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: VTUQ | Statement: [Nakhon Ratchasima air base, hasICAOCode, VTUQ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VTUQ Context triple: [Nakhon Ratchasima air base, hasICAOCode, VTUQ]
-
A.
QVT
QVT (Query/View/Transformation) is an OMG standard language for specifying model-to-model transformations in model-driven software engineering.
-
B.
QAVS
QAVS is a prestigious UK national honour that recognises outstanding voluntary groups for their exceptional service to local communities.
-
C.
VTST
VTST is the station code for the Vermont/Sunset station on the Los Angeles Metro Rail system.
-
D.
VUT
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
-
E.
VUT
VUT is the Czech abbreviation for Brno University of Technology, a major technical and engineering university based in Brno, Czech Republic.
- 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: VTUQ Triple: [Nakhon Ratchasima air base, hasICAOCode, VTUQ]
Generated description
VTUQ is the ICAO airport code assigned to Nakhon Ratchasima Air Base in Thailand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VTUQ Target entity description: VTUQ is the ICAO airport code assigned to Nakhon Ratchasima Air Base in Thailand.
-
A.
QVT
QVT (Query/View/Transformation) is an OMG standard language for specifying model-to-model transformations in model-driven software engineering.
-
B.
QAVS
QAVS is a prestigious UK national honour that recognises outstanding voluntary groups for their exceptional service to local communities.
-
C.
VTST
VTST is the station code for the Vermont/Sunset station on the Los Angeles Metro Rail system.
-
D.
VUT
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
-
E.
VUT
VUT is the Czech abbreviation for Brno University of Technology, a major technical and engineering university based in Brno, Czech Republic.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9805125e481908ed56f708de98a9e |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd8f1308190992c0bd832e1b05e |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd98d29c8190b33cb2cc6c477b1d |
completed | May 3, 2026, 4:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ce2c7630819091433543dfdf8402 |
completed | May 3, 2026, 4:25 a.m. |
Created at: April 9, 2026, 8:57 p.m.