Triple

T1248844
Position Surface form Disambiguated ID Type / Status
Subject GPS E26827 entity
Predicate accuracyCivilianTypical P25786 FINISHED
Object About 5 to 10 meters LITERAL 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: About 5 to 10 meters | Statement: [GPS, accuracyCivilianTypical, About 5 to 10 meters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: accuracyCivilianTypical
Context triple: [GPS, accuracyCivilianTypical, About 5 to 10 meters]
  • A. civilianUse
    Indicates that something is intended for, suitable for, or actually used by civilians rather than military or combat purposes.
  • B. civilianTarget
    Indicates that the action or operation is directed at, affects, or designates civilians or civilian objects as the target.
  • C. isCivilian
    Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
  • D. typicalIn
    Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
  • E. civilianImpact
    Indicates the extent to which an action, event, or situation affects civilians, especially in terms of harm, disruption, or other consequences.
  • F. None of above. chosen

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_69a49487a9c48190ba9b05348fd1b53f completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf827e088190a16d845cea14f2c9 completed March 1, 2026, 10:36 p.m.
PD Predicate disambiguation batch_69a4bb6b075881908e867c25b5080e25 completed March 1, 2026, 10:19 p.m.
PDg Predicate description generation batch_69a4bc49693c8190978ec63a5171d342 completed March 1, 2026, 10:23 p.m.
Created at: March 1, 2026, 7:47 p.m.