Triple

T8690039
Position Surface form Disambiguated ID Type / Status
Subject Lumut E206262 entity
Predicate partOf P40 FINISHED
Object Manjung District E668307 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: Manjung District | Statement: [Lumut, partOf, Manjung District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manjung District
Context triple: [Lumut, partOf, Manjung District]
  • A. Manjung District chosen
    Manjung District is a coastal administrative district in the state of Perak, Malaysia, known for its maritime economy, tourism, and nearby island destinations.
  • B. Kuala Pilah District
    Kuala Pilah District is an inland administrative district in the Malaysian state of Negeri Sembilan, known for its traditional Minangkabau cultural heritage and rural landscapes.
  • C. Langkawi District
    Langkawi District is an administrative district in the state of Kedah, Malaysia, encompassing the popular tourist islands of the Langkawi archipelago.
  • D. Seremban District
    Seremban District is an administrative district in the Malaysian state of Negeri Sembilan that includes the state capital, Seremban, as its main urban center.
  • E. Bentong District
    Bentong District is an administrative district in western Pahang, Malaysia, known for its hilly terrain, cool climate, and agricultural products such as ginger and durian.
  • 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5734602c81909a0687e00f4a4a26 completed March 31, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfab417d4481908cc6305ec2752078 completed April 3, 2026, 11:57 a.m.
Created at: March 30, 2026, 6:33 p.m.