Triple

T10029741
Position Surface form Disambiguated ID Type / Status
Subject Cameron Highlands E204821 entity
Predicate town P3385 FINISHED
Object Tanah Rata E839183 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: Tanah Rata | Statement: [Cameron Highlands, town, Tanah Rata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanah Rata
Context triple: [Cameron Highlands, town, Tanah Rata]
  • A. Tanah Rata chosen
    Tanah Rata is a hill town in Malaysia’s Cameron Highlands known as a central hub for tourism, accommodation, and access to the region’s tea plantations and cool-climate attractions.
  • B. Kuala Kangsar
    Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
  • C. Ratekau
    Ratekau is a municipality in the district of Ostholstein in Schleswig-Holstein, northern Germany, near the Baltic Sea coast.
  • D. Temerloh
    Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
  • E. Kuala Pilah
    Kuala Pilah is a historic inland town in the Malaysian state of Negeri Sembilan, known for its traditional Minangkabau cultural heritage and role as an administrative and commercial center for the surrounding rural district.
  • 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.