Triple

T10103436
Position Surface form Disambiguated ID Type / Status
Subject Segamat E216257 entity
Predicate hasNearbyLocality P3883 FINISHED
Object Muar E218122 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: Muar | Statement: [Segamat, hasNearbyLocality, Muar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muar
Context triple: [Segamat, hasNearbyLocality, Muar]
  • A. Muar chosen
    Muar is a historic riverside town and important commercial center in the Malaysian state of Johor, known for its colonial architecture, food culture, and coffee shops.
  • B. Muar River
    The Muar River is a major river in southern Peninsular Malaysia that flows through several districts before emptying into the Strait of Malacca.
  • C. Johor River
    The Johor River is a major waterway in the southern Malaysian state of Johor, historically significant as a strategic and economic lifeline for the region.
  • D. Bachok
    Bachok is a coastal town and district in the Malaysian state of Kelantan, known for its beaches and traditional Malay fishing villages.
  • E. Kelantan River
    The Kelantan River is a major waterway in northeastern Peninsular Malaysia that flows through the state of Kelantan into the South China Sea, playing a key role in the region’s ecology, agriculture, and settlements.
  • 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_69ca83d039f08190b9d10363221c69fb completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd09af07c819099774af46ebf62d7 completed April 2, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3005e007881909f40575d129f2c3d completed April 6, 2026, 12:37 a.m.
Created at: March 30, 2026, 9:03 p.m.