Triple

T21218954
Position Surface form Disambiguated ID Type / Status
Subject Universitas Pekalongan E522913 entity
Predicate locatedIn P40 FINISHED
Object Pekalongan 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: Pekalongan | Statement: [Universitas Pekalongan, locatedIn, Pekalongan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pekalongan
Context triple: [Universitas Pekalongan, locatedIn, Pekalongan]
  • A. Pekalongan chosen
    Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
  • B. Tegal
    Tegal is a coastal city in Central Java, Indonesia, known as a regional transport hub and trading center on the north coast railway line.
  • C. Purwokerto
    Purwokerto is a major town in Central Java, Indonesia, known as a regional economic and educational center and a gateway to nearby highland tourist destinations.
  • D. Purworejo
    Purworejo is a regency in Central Java, Indonesia, known for its agricultural landscape and proximity to the southern coast of Java.
  • E. Blora
    Blora is a regency-level town in Indonesia known for its teak forests and cultural heritage, located in the eastern part of Central Java.
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73476d93481909c6c99dcc0b16123 completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:42 p.m.