Triple

T2686092
Position Surface form Disambiguated ID Type / Status
Subject Sabah E57487 entity
Predicate contains P35 FINISHED
Object Sandakan E112556 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: Sandakan | Statement: [Sabah, contains, Sandakan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandakan
Context triple: [Sabah, contains, Sandakan]
  • A. Sandakan chosen
    Sandakan is a coastal city in Sabah, Malaysia, known historically as a major port and gateway to the biodiverse rainforests and wildlife of Borneo.
  • B. Kota Kinabalu
    Kota Kinabalu is a coastal city in Malaysian Borneo known as the gateway to Mount Kinabalu and the biodiverse rainforests and marine parks of Sabah.
  • C. Kuching
    Kuching is the capital and largest city of the Malaysian state of Sarawak on the island of Borneo, known for its diverse culture, colonial architecture, and proximity to rainforest and wildlife attractions.
  • D. 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.
  • E. 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.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9ef2fe0819082bbe746ca682a7e completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc63b76e0819084c4d2bd4a9e6d78 completed March 10, 2026, 7:20 a.m.
Created at: March 6, 2026, 9:54 p.m.