Triple

T7545338
Position Surface form Disambiguated ID Type / Status
Subject Manosque E178386 entity
Predicate populationRankInAlpesDeHauteProvence P45844 FINISHED
Object largest town in the department 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: largest town in the department | Statement: [Manosque, populationRankInAlpesDeHauteProvence, largest town in the department]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: populationRankInAlpesDeHauteProvence
Context triple: [Manosque, populationRankInAlpesDeHauteProvence, largest town in the department]
  • A. populationRankInCanton
    Indicates the relative position of an entity in terms of population size compared to other entities within the same canton.
  • B. populationRankInFrance
    Indicates the relative position of an entity in an ordered list based on its population size within France.
  • C. rankingByLengthInAlps
    Indicates an ordering of entities based on their relative lengths specifically within the context of the Alps.
  • D. hasPopulationRankInDepartment chosen
    Indicates the relative position of an entity’s population size compared to other entities within the same department.
  • E. hasPopulationRankInSwitzerland
    Indicates the relative position of an entity in the ordered list of populations within Switzerland, such as its rank by population size compared to other Swiss entities.
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f898069881909fa8f9c885c4565b completed March 27, 2026, 9:37 p.m.
PD Predicate disambiguation batch_69c6f4daad6c8190af2b8ae88d2c8cb7 completed March 27, 2026, 9:21 p.m.
Created at: March 27, 2026, 3:48 p.m.