Triple

T20606519
Position Surface form Disambiguated ID Type / Status
Subject Province of Central Java E506325 entity
Predicate containsCity P294 FINISHED
Object Tegal E372519 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: Tegal | Statement: [Province of Central Java, containsCity, Tegal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegal
Context triple: [Province of Central Java, containsCity, Tegal]
  • A. Tegal chosen
    Tegal is a coastal city in Central Java, Indonesia, known as a regional transport hub and trading center on the north coast railway line.
  • B. Semarang
    Semarang is a major coastal city on the north coast of Java in Indonesia, known historically as an important colonial trading hub and now as a significant commercial and industrial center.
  • C. Pekalongan
    Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
  • D. Tegal Regency
    Tegal Regency is an administrative region in Central Java, Indonesia, known for its agricultural economy, coastal areas along the Java Sea, and cultural ties to the city of Tegal.
  • E. 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.
  • 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_69e0b4bb2b4081908fa4a72444120f35 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aad394e8819080185187a8b3de93 completed April 20, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0986cd87d48190b6926ac8eb2d5a35 completed May 17, 2026, 9:13 a.m.
Created at: April 16, 2026, 11:41 a.m.