Triple

T9630282
Position Surface form Disambiguated ID Type / Status
Subject Kluang E232783 entity
Predicate hasNearbyTown P3883 FINISHED
Object Batu Pahat E274277 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: Batu Pahat | Statement: [Kluang, hasNearbyTown, Batu Pahat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batu Pahat
Context triple: [Kluang, hasNearbyTown, Batu Pahat]
  • A. Batu Pahat chosen
    Batu Pahat is a coastal town and important commercial and industrial hub in the Malaysian state of Johor.
  • B. Seremban
    Seremban is the capital city of the Malaysian state of Negeri Sembilan, known as an administrative, commercial, and cultural center in the western part of Peninsular Malaysia.
  • C. Kuala Kangsar
    Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
  • D. Temerloh
    Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
  • E. Gombak
    Gombak is a district in the state of Selangor, Malaysia, located within the greater Kuala Lumpur metropolitan area in the Klang Valley.
  • 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_69ca848940cc8190b97cec654cb3bb4a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b01863c8190a9ec4684804f96bc completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d28194f6e88190932efe607088394a completed April 5, 2026, 3:36 p.m.
Created at: March 30, 2026, 8:11 p.m.