Triple

T27052434
Position Surface form Disambiguated ID Type / Status
Subject Barham E684808 entity
Predicate locatedOppositeTown P192729 FINISHED
Object Koondrook NE NERFINISHED

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: Koondrook | Statement: [Barham, locatedOppositeTown, Koondrook]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: locatedOppositeTown
Context triple: [Barham, locatedOppositeTown, Koondrook]
  • A. oppositeTownCountry
    Indicates that two locations are situated in opposing or contrasting town and country settings, such that one is urban while the other is rural.
  • B. oppositeTownAcrossBorder
    Indicates that one town is located directly across a border from another town, positioned as its opposite counterpart.
  • C. oppositeMunicipality chosen
    Indicates that two municipalities are located opposite each other, typically across a boundary such as a river, bay, or other separating feature.
  • D. oppositeCityCountry
    Indicates that a city and a country are located on opposite sides of the world or in geographically opposing regions relative to each other.
  • E. hasNearbyTown
    Indicates that one location has a town situated close to it in geographic proximity.
  • F. None of above.

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_69ef14829fac8190914bef9ecc3005d7 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69fe78e545888190a239af1a84280fa0 completed May 8, 2026, 11:59 p.m.
PD Predicate disambiguation batch_69fe7842742081908043eb950ed69f92 completed May 8, 2026, 11:56 p.m.
Created at: April 27, 2026, 8:15 a.m.