Triple

T26462272
Position Surface form Disambiguated ID Type / Status
Subject Yellow Dragon Sports Center Stadium E665668 entity
Predicate alsoKnownAs P39 FINISHED
Object Huanglong Sports Center Stadium
Huanglong Sports Center Stadium is a large multi-purpose sports venue in Hangzhou, China, primarily used for football matches and major athletic events.
E1726735 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: Huanglong Sports Center Stadium | Statement: [Yellow Dragon Sports Center Stadium, alsoKnownAs, Huanglong Sports Center Stadium]
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: Huanglong Sports Center Stadium
Triple: [Yellow Dragon Sports Center Stadium, alsoKnownAs, Huanglong Sports Center Stadium]
Generated description
Huanglong Sports Center Stadium is a large multi-purpose sports venue in Hangzhou, China, primarily used for football matches and major athletic events.

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_69ee883e812c8190a9b5a9cdb87fee5e completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6129651808190b715548c968b3c22 completed May 2, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aeddce848190befd9c838123f53a completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11b29dd1a88190924fd07ab6dfa941 completed May 23, 2026, 1:58 p.m.
NED2 Entity disambiguation (via description) batch_6a11b345d944819096ecca996841404f completed May 23, 2026, 2:01 p.m.
Created at: April 27, 2026, 12:13 a.m.