Triple

T9012976
Position Surface form Disambiguated ID Type / Status
Subject Klang Valley E215519 entity
Predicate containsCity P294 FINISHED
Object Bangi E762915 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: Bangi | Statement: [Klang Valley, containsCity, Bangi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangi
Context triple: [Klang Valley, containsCity, Bangi]
  • A. Bangi chosen
    Bangi is a town in the state of Selangor, Malaysia, known as an educational hub due to the presence of major institutions and research facilities.
  • B. Dengkil
    Dengkil is a town in the Sepang District of Selangor, Malaysia, known for its proximity to Putrajaya and Kuala Lumpur International Airport.
  • C. Bachok
    Bachok is a coastal town and district in the Malaysian state of Kelantan, known for its beaches and traditional Malay fishing villages.
  • D. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • E. Jasinga
    Jasinga is a district-level area in West Java, Indonesia, known as one of the administrative regions within Bogor Regency.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69f96980819093bfc49d48570c65 completed April 1, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdba11a6481909cac624530a77ffe completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:06 p.m.