Triple

T11998277
Position Surface form Disambiguated ID Type / Status
Subject Downtown Core E285585 entity
Predicate borders P224 FINISHED
Object Rochor E805950 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: Rochor | Statement: [Downtown Core, borders, Rochor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rochor
Context triple: [Downtown Core, borders, Rochor]
  • A. Rochor chosen
    Rochor is a central urban planning area and historic district in Singapore known for its mix of heritage sites, commercial activity, and dense public housing.
  • B. Băneasa
    Băneasa is a northern district of Bucharest, Romania, known for its residential areas, shopping centers, and proximity to Băneasa Airport and Băneasa Forest.
  • C. Băneasa
    Băneasa is a commune in southeastern Romania, located in Constanța County near the border with Bulgaria.
  • D. Râmnicu Sărat
    Râmnicu Sărat is a town in eastern Romania, historically known as a market and military center and for the nearby former political prison that operated during the communist era.
  • E. Otopeni
    Otopeni is a town in Ilfov County, Romania, just north of Bucharest, best known for hosting the country’s main international airport.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c172788190b92042e9d10a48bf completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f640b9a481908de1b7858e3db52c completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:46 p.m.