Triple

T23594536
Position Surface form Disambiguated ID Type / Status
Subject All in My Head (Flex) E582576 entity
Predicate usesInterpolation P91539 FINISHED
Object true 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: true | Statement: [All in My Head (Flex), usesInterpolation, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesInterpolation
Context triple: [All in My Head (Flex), usesInterpolation, true]
  • A. usesInterpolationFrom
    Indicates that one entity derives or computes its values by applying interpolation based on data or parameters obtained from another entity.
  • B. supportsInterpolation
    Indicates that one entity provides the capability to perform interpolation operations on another entity or its data.
  • C. hasInterpolation
    Indicates that one value, state, or representation is derived from others by applying an interpolation method between them.
  • D. hasNotableInterpolationIn
    Indicates that one entity contains a significant or noteworthy interpolation, insertion, or embedded segment within the other entity.
  • E. usesSamplingOrInterpolation chosen
    Indicates that one entity applies sampling or interpolation techniques to obtain or approximate values from another entity or dataset.
  • 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_69e248f9e0a08190814772847003b1ff completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b08e9aa4819091099dfc2074b22d completed April 29, 2026, 7:17 a.m.
PD Predicate disambiguation batch_69f118c96a0081908a8ac98ef7e7e60c completed April 28, 2026, 8:30 p.m.
Created at: April 17, 2026, 6:42 p.m.