Triple

T17124698
Position Surface form Disambiguated ID Type / Status
Subject Carlingford Lough E415561 entity
Predicate hasNearbyTown P3883 FINISHED
Object Greenore E894177 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: Greenore | Statement: [Carlingford Lough, hasNearbyTown, Greenore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greenore
Context triple: [Carlingford Lough, hasNearbyTown, Greenore]
  • A. Greenore chosen
    Greenore is a small coastal village and port on Carlingford Lough in County Louth, Ireland, historically known for its ferry services and railway connections.
  • B. Borrisokane
    Borrisokane is a small rural town in northern County Tipperary, Ireland, known for its agricultural surroundings and traditional Irish community character.
  • C. Penco
    Penco is a coastal Chilean city and commune in the Biobío Region, historically known as the original site of the city of Concepción.
  • D. Ore
    Ore is a suburb and railway station area in Hastings, East Sussex, England, serving as a local residential and transport hub.
  • E. Maden
    Maden is a town and district in eastern Turkey known historically for its mining activities and mountainous terrain.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f025fce481908e261f2e363e14f9 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a12a7288190911c1be2667916c0 completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:36 a.m.