Triple

T14707175
Position Surface form Disambiguated ID Type / Status
Subject Moat Cailin E345455 entity
Predicate travelSignificance P87607 FINISHED
Object bottleneck for armies moving between regions 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: bottleneck for armies moving between regions | Statement: [Moat Cailin, travelSignificance, bottleneck for armies moving between regions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: travelSignificance
Context triple: [Moat Cailin, travelSignificance, bottleneck for armies moving between regions]
  • A. travelClassRelevance
    Indicates the degree to which a particular travel class (e.g., economy, business) is pertinent or applicable within a given travel context or scenario.
  • B. travelCharacteristic chosen
    Indicates a quality, feature, or attribute that characterizes how travel or movement is conducted or experienced.
  • C. travelScope
    Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
  • D. tourScale
    Indicates the relative size, scope, or extent of a tour in comparison to other tours or a standard reference.
  • E. tourismImportance
    Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb609965081908f654bcb9eaaa145 completed April 14, 2026, 9:47 p.m.
PD Predicate disambiguation batch_69de657c57ec8190ae0b9bb79a514566 completed April 14, 2026, 4:04 p.m.
Created at: April 10, 2026, 1:28 a.m.