Triple

T9382035
Position Surface form Disambiguated ID Type / Status
Subject Thuận Thành District E225808 entity
Predicate capital P234 FINISHED
Object Hồ town E794362 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: Hồ town | Statement: [Thuận Thành District, capital, Hồ town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hồ town
Context triple: [Thuận Thành District, capital, Hồ town]
  • A. Hồ town chosen
    Hồ town is the principal urban and administrative hub of Thuận Thành District in Vietnam.
  • B. Hương Thủy Town
    Hương Thủy Town is a district-level town in central Vietnam known for its proximity to the historic city of Huế in Thừa Thiên Huế Province.
  • C. Gucun Town
    Gucun Town is a suburban township in Shanghai, China, known for its large Gucun Park and residential communities within Baoshan District.
  • D. Tam Đảo town
    Tam Đảo town is a popular mountainous resort destination in northern Vietnam, known for its cool climate, misty scenery, and French colonial-era architecture.
  • E. Mỹ Hào town
    Mỹ Hào town is an urban administrative center in northern Vietnam’s Hưng Yên Province, known for its developing industry and proximity to Hanoi.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca842e9dcc8190a264119e683cfe04 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd50be52248190bc7cd9deb95a1ef8 completed April 1, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d100ddec0c8190854fb5db36e840db completed April 4, 2026, 12:15 p.m.
Created at: March 30, 2026, 7:44 p.m.