Triple

T10707093
Position Surface form Disambiguated ID Type / Status
Subject Sungai Petani E252435 entity
Predicate nearbyCity P350 FINISHED
Object Alor Setar E247312 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: Alor Setar | Statement: [Sungai Petani, nearbyCity, Alor Setar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alor Setar
Context triple: [Sungai Petani, nearbyCity, Alor Setar]
  • A. Alor Setar chosen
    Alor Setar is a major city in northwestern Peninsular Malaysia known as an administrative, cultural, and commercial hub near the border with Thailand.
  • B. Shah Alam
    Shah Alam is a planned city in Malaysia known as the administrative and commercial center of the state of Selangor.
  • C. Bandar Seri Jempol
    Bandar Seri Jempol is a principal town and local commercial hub in the Jempol District of Negeri Sembilan, Malaysia.
  • D. Sungai Petani
    Sungai Petani is a major commercial and residential town in the Malaysian state of Kedah, known as one of its largest and most rapidly developing urban centers.
  • E. Kuantan
    Kuantan is a coastal city on the east coast of Peninsular Malaysia known as a major economic and cultural center and gateway to the South China Sea.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fde080d48190830eaa863aad61ff completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69de847e0ee48190a4c1470fc5296213 completed April 14, 2026, 6:16 p.m.
Created at: April 8, 2026, 9:12 p.m.