Triple

T25033732
Position Surface form Disambiguated ID Type / Status
Subject Terminal 1 (Changsha Huanghua International Airport) E626919 entity
Predicate hasName P744 FINISHED
Object Terminal 1
Terminal 1 at Changsha Huanghua International Airport is a passenger terminal building that handles domestic and regional flights for the airport serving Changsha, Hunan, China.
E626919 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: Terminal 1 | Statement: [Terminal 1 (Changsha Huanghua International Airport), hasName, Terminal 1]
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: Terminal 1
Triple: [Terminal 1 (Changsha Huanghua International Airport), hasName, Terminal 1]
Generated description
Terminal 1 at Changsha Huanghua International Airport is a passenger terminal building that handles domestic and regional flights for the airport serving Changsha, Hunan, China.

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_69e2ff2a2c088190be513727ee8bfe78 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44f71778c8190ab36b2e6faf98056 completed May 1, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048ac46c88190850c8a7826724ae1 completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a104a450fe08190bb6f266341f1f595 completed May 22, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc667e48190bb0feadc5b324cde completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 6:07 a.m.