Triple

T27243095
Position Surface form Disambiguated ID Type / Status
Subject Huaihua Municipal People's Government E687263 entity
Predicate governsAdministrativeDivisions P82358 FINISHED
Object Huitong County
Huitong County is an administrative county in Hunan Province, China, under the jurisdiction of the prefecture-level city of Huaihua.
E1789440 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: Huitong County | Statement: [Huaihua Municipal People's Government, governsAdministrativeDivisions, Huitong County]
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: Huitong County
Triple: [Huaihua Municipal People's Government, governsAdministrativeDivisions, Huitong County]
Generated description
Huitong County is an administrative county in Hunan Province, China, under the jurisdiction of the prefecture-level city of Huaihua.

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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6267ec0788190800c54cc2388370f completed May 2, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ec8db6f081909c96d78bb41defd1 completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ee3f436c8190b1daf7ec5041304e completed May 24, 2026, 12:25 p.m.
NED2 Entity disambiguation (via description) batch_6a12eef15e2c819099088626fb78adce completed May 24, 2026, 12:28 p.m.
Created at: April 27, 2026, 10:39 a.m.