Triple

T552199
Position Surface form Disambiguated ID Type / Status
Subject Hebei E11863 entity
Predicate surrounds P7850 FINISHED
Object Tianjin E31338 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: Tianjin | Statement: [Hebei, surrounds, Tianjin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tianjin
Context triple: [Hebei, surrounds, Tianjin]
  • A. Tianjin chosen
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • B. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • C. Shanghai
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • D. Port of Tianjin
    The Port of Tianjin is one of China’s largest and busiest seaports, serving as a major maritime gateway to Beijing and the industrial north.
  • E. Baoding
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499047bd4819089ca8345f1b6e46c completed March 1, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc5ee996081908fba19d8d141a779 completed March 8, 2026, 12:42 a.m.
Created at: March 1, 2026, 7:32 p.m.