Triple

T34793824
Position Surface form Disambiguated ID Type / Status
Subject Transverse Mercator E1003014 entity
Predicate zoneNumbering P181623 FINISHED
Object used in UTM to identify longitudinal strips 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: used in UTM to identify longitudinal strips | Statement: [Transverse Mercator, zoneNumbering, used in UTM to identify longitudinal strips]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: zoneNumbering
Context triple: [Transverse Mercator, zoneNumbering, used in UTM to identify longitudinal strips]
  • A. zoneNumberRange
    Indicates that there is an associated range of zone numbers, typically specifying the minimum and maximum zone identifiers applicable in a given context.
  • B. zoneCount
    Indicates the number of distinct zones associated with or contained within a given entity or context.
  • C. zoneLabel
    Indicates that a specific label or name is assigned to a defined zone or area within a larger context.
  • D. regionNumber
    Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
  • E. zoneBased
    Indicates that the relationship or action is determined or constrained by specific geographic or logical zones.
  • 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_69f76db543808190b188c6c86a91491b completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77ffa6b68819090257fed3802c239 completed May 3, 2026, 5:03 p.m.
PD Predicate disambiguation batch_69f7795978c481909e152cd1bd02dd07 completed May 3, 2026, 4:35 p.m.
PDg Predicate description generation batch_69f77ff804f08190b431a31e6179ace4 completed May 3, 2026, 5:03 p.m.
Created at: May 3, 2026, 3:59 p.m.