Triple

T30461654
Position Surface form Disambiguated ID Type / Status
Subject Shanwei E775029 entity
Predicate hasCountyLevelDivision P747 FINISHED
Object Luhe County
Luhe County is a county-level administrative division under the jurisdiction of Shanwei City in Guangdong Province, China, known for its predominantly rural character and Hakka cultural heritage.
E2078349 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: Luhe County | Statement: [Shanwei, hasCountyLevelDivision, Luhe 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: Luhe County
Triple: [Shanwei, hasCountyLevelDivision, Luhe County]
Generated description
Luhe County is a county-level administrative division under the jurisdiction of Shanwei City in Guangdong Province, China, known for its predominantly rural character and Hakka cultural heritage.

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_69f2249622a48190b1fae2e3e4ee958a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f686f0d838819099ca4d828a246d7f completed May 2, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a36a0063e5481908fcf1e3485eb9c93 completed June 20, 2026, 2:13 p.m.
NEDg Description generation batch_6a36a0aca11c819086048e5576562c17 completed June 20, 2026, 2:16 p.m.
NED2 Entity disambiguation (via description) batch_6a36a14c54688190bac4066ddea8afde completed June 20, 2026, 2:18 p.m.
Created at: April 29, 2026, 8:10 p.m.