Triple

T5549596
Position Surface form Disambiguated ID Type / Status
Subject Quang Ngai Province E145492 entity
Predicate hasSettlement P1068 FINISHED
Object Quang Ngai City E532752 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: Quang Ngai City | Statement: [Quang Ngai Province, hasSettlement, Quang Ngai City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quang Ngai City
Context triple: [Quang Ngai Province, hasSettlement, Quang Ngai City]
  • A. Quang Ngai City chosen
    Quang Ngai City is an urban center in central Vietnam known as the political, economic, and cultural hub of Quang Ngai Province.
  • B. Nam Dinh City
    Nam Dinh City is the capital and largest urban center of Nam Dinh Province in northern Vietnam, known historically as an important cultural and industrial hub in the Red River Delta.
  • C. Hà Tiên
    Hà Tiên is a coastal town in southwestern Vietnam near the Cambodian border, known historically as a trading port and cultural crossroads in the Mekong Delta region.
  • D. Phan Rang
    Phan Rang is a coastal city in south-central Vietnam, known historically as a Cham cultural center and now as the capital of Ninh Thuận Province.
  • E. Phong Điền
    Phong Điền is a rural district of Cần Thơ in Vietnam’s Mekong Delta, known for its lush orchards and traditional floating markets.
  • 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_69c008fb879c81909f5bfa56fadc1d46 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01fe143ec8190bb67d2530c92a419 completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04cf6d9f48190a3ee3446973c7381 completed March 22, 2026, 8:11 p.m.
Created at: March 22, 2026, 3:35 p.m.