Triple

T30208983
Position Surface form Disambiguated ID Type / Status
Subject The Shots E768015 entity
Predicate associatedWithMilitaryTown P139461 FINISHED
Object Aldershot E60600 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: Aldershot | Statement: [The Shots, associatedWithMilitaryTown, Aldershot]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithMilitaryTown
Context triple: [The Shots, associatedWithMilitaryTown, Aldershot]
  • A. associatedWithMilitaryHistory
    Indicates a relationship in which something is connected or relevant to military history, such as events, figures, institutions, or artifacts.
  • B. hasNearbyMilitaryTown chosen
    Indicates that one location is situated close to a town whose primary function or identity is associated with military presence or activity.
  • C. hasMilitaryAssociation
    Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
  • D. associatedWithWar
    Indicates a relationship where an entity is connected or related to war, such as by involvement, influence, cause, or context.
  • E. associatedWithMilitaryConquests
    Indicates a relationship where an entity is connected to, involved in, or characterized by military conquests or campaigns.
  • F. None of above.

Provenance (4 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_69f2247eb0848190b4032f302d39c0d9 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_6a037c876524819098545e6037d3107d completed May 12, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ee715e4819081459592b3fb7562 completed June 9, 2026, 1:39 a.m.
PD Predicate disambiguation batch_6a0379e0f3d88190a4ee7b0673f1ef90 completed May 12, 2026, 7:05 p.m.
Created at: April 29, 2026, 7:32 p.m.