Triple

T17802702
Position Surface form Disambiguated ID Type / Status
Subject Harbin Institute of Technology E444473 entity
Predicate locatedIn P40 FINISHED
Object Harbin NE NERFINISHED

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: Harbin | Statement: [Harbin Institute of Technology, locatedIn, Harbin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harbin
Context triple: [Harbin Institute of Technology, locatedIn, Harbin]
  • A. Harbin chosen
    Harbin is a major city in northeastern China known for its Russian-influenced architecture and its internationally famous annual ice and snow festival.
  • B. Qiqihar
    Qiqihar is a major industrial city in northeastern China’s Heilongjiang province, known historically as a regional transportation hub and center for heavy industry.
  • C. Jiamusi
    Jiamusi is a prefecture-level city in northeastern China’s Heilongjiang province, known as an important regional industrial and transportation hub.
  • D. Hegang
    Hegang is a coal-mining city in northeastern Heilongjiang Province, China, located near the Russian border along the Amur River region.
  • E. Mudanjiang
    Mudanjiang is a prefecture-level city in southeastern Heilongjiang Province in northeastern China, known as a regional transport hub and gateway to nearby scenic and border areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4880171608190be2088c7a387bfb7 completed April 19, 2026, 7:45 a.m.
Created at: April 10, 2026, 10:13 a.m.