Triple

T1054075
Position Surface form Disambiguated ID Type / Status
Subject Burmese python E22761 entity
Predicate sensoryAdaptation P2375 FINISHED
Object heat-sensing pits along the lips 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: heat-sensing pits along the lips | Statement: [Burmese python, sensoryAdaptation, heat-sensing pits along the lips]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sensoryAdaptation
Context triple: [Burmese python, sensoryAdaptation, heat-sensing pits along the lips]
  • A. adaptation
    Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
  • B. adaptationType chosen
    Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
  • C. isFrequentlyAdapted
    Indicates that a work or source material is often transformed or re-created into new formats or versions, such as films, plays, or other media.
  • D. primarySense
    Indicates that one sense or meaning of an entity is designated as its main or most central sense among possible alternatives.
  • E. adaptationStatus
    Indicates the current state or progress of how something has been adapted or adjusted in response to specific conditions, requirements, or contexts.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8d669448190955507e2e4975b9f completed March 1, 2026, 10:08 p.m.
PD Predicate disambiguation batch_69a4b731e25c8190b5ea8466648c2c9a completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.