Triple

T4149521
Position Surface form Disambiguated ID Type / Status
Subject Pekanbaru E89869 entity
Predicate locatedIn P40 FINISHED
Object Sumatra E14825 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: Sumatra | Statement: [Pekanbaru, locatedIn, Sumatra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sumatra
Context triple: [Pekanbaru, locatedIn, Sumatra]
  • A. Sumatra chosen
    Sumatra is a large Indonesian island in western Indonesia known for its rich biodiversity, active volcanoes, and significant role in regional trade and history.
  • B. North Sumatra
    North Sumatra is a populous province on the Indonesian island of Sumatra, known for its diverse cultures, Lake Toba, and the city of Medan as its capital.
  • C. Kalimantan
    Kalimantan is the Indonesian portion of the island of Borneo, known for its vast rainforests, rich biodiversity, and significant natural resources.
  • D. Isle of Java
    Isle of Java is a coffee-focused quick-service location at Disney’s Discovery Island, known for serving beverages and light refreshments to park guests.
  • E. Greater Sunda Islands
    The Greater Sunda Islands are a major group of large islands in maritime Southeast Asia, including Java, Sumatra, Borneo, and Sulawesi, known for their rich biodiversity and dense human populations.
  • 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_69aed95a59a881909b26e70b42c6811a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0273a038819087db092da234e767 completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f29865c8190b0ecb7acc9901765 completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:43 p.m.