Triple

T10029682
Position Surface form Disambiguated ID Type / Status
Subject Pahang State Legislative Assembly E204820 entity
Predicate meetsIn P40 FINISHED
Object Kuantan E239855 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: Kuantan | Statement: [Pahang State Legislative Assembly, meetsIn, Kuantan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuantan
Context triple: [Pahang State Legislative Assembly, meetsIn, Kuantan]
  • A. Kuantan chosen
    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.
  • B. Kota Bharu
    Kota Bharu is a major city in northeastern Peninsular Malaysia known for its rich Malay culture, traditional markets, and role as the administrative and commercial center of Kelantan state.
  • C. Alor Setar
    Alor Setar is a major city in northwestern Peninsular Malaysia known as an administrative, cultural, and commercial hub near the border with Thailand.
  • D. Kulim
    Kulim is a prominent town and industrial hub in the Malaysian state of Kedah, known for its high-tech manufacturing and proximity to Penang.
  • E. Kuala Kangsar
    Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
  • 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_69ca834d77188190ad645e33e8ca3200 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcde69bd08190a5c79ec8487dfff6 completed April 2, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b60256b48190829cfdbff0105cc0 completed April 5, 2026, 7:20 p.m.
Created at: March 30, 2026, 8:54 p.m.