Triple

T27503379
Position Surface form Disambiguated ID Type / Status
Subject VTBU E694216 entity
Predicate civilOperator P57533 FINISHED
Object U-Tapao International Aviation Company Limited
U-Tapao International Aviation Company Limited is the company responsible for managing and operating U-Tapao International Airport in Thailand.
E1776064 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: U-Tapao International Aviation Company Limited | Statement: [VTBU, civilOperator, U-Tapao International Aviation Company Limited]
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: U-Tapao International Aviation Company Limited
Triple: [VTBU, civilOperator, U-Tapao International Aviation Company Limited]
Generated description
U-Tapao International Aviation Company Limited is the company responsible for managing and operating U-Tapao International Airport in Thailand.

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_69ef538370888190b1ddf53bb4831188 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62ec49d5481909350801bd603a5b0 completed May 2, 2026, 5:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbf8fabc81909c4d133548e75dff completed May 24, 2026, 8:51 a.m.
NEDg Description generation batch_6a12bd4dacfc81908c61517b7286c35d completed May 24, 2026, 8:56 a.m.
NED2 Entity disambiguation (via description) batch_6a12bdeacda08190bfe8354ed2666d23 completed May 24, 2026, 8:59 a.m.
Created at: April 27, 2026, 1:12 p.m.