Triple

T23449697
Position Surface form Disambiguated ID Type / Status
Subject Liujiang River E567742 entity
Predicate flowsThrough P225 FINISHED
Object Laibin 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: Laibin | Statement: [Liujiang River, flowsThrough, Laibin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laibin
Context triple: [Liujiang River, flowsThrough, Laibin]
  • A. Laibin chosen
    Laibin is a prefecture-level city in south-central China known for its role as a regional transportation hub and its mix of industrial and agricultural development.
  • B. Laibok
    Laibok is the principal city and governmental center of the Andorian homeworld in the Star Trek universe.
  • C. Lubja
    Lubja is a small village located within Viimsi Parish in northern Estonia, near the capital city of Tallinn.
  • D. Licinia
    Licinia was a Roman noblewoman of the late Republic, known primarily as the daughter of Mucia Tertia and thus connected to prominent political families of her time.
  • E. Ludza
    Ludza is one of the principal towns of the Latgale region in eastern Latvia, known for its historic castle ruins and status as one of the country’s oldest settlements.
  • 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_69e2458b4c888190b1d7998f9862a558 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a64c1ee081908ba3adf5ce80d6a5 completed April 29, 2026, 6:33 a.m.
Created at: April 17, 2026, 5:52 p.m.