Triple

T461730
Position Surface form Disambiguated ID Type / Status
Subject Hanbury Brown and Twiss effect E7352 entity
Predicate measurementMethod P859 FINISHED
Object correlation of intensity fluctuations at two detectors 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: correlation of intensity fluctuations at two detectors | Statement: [Hanbury Brown and Twiss effect, measurementMethod, correlation of intensity fluctuations at two detectors]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: measurementMethod
Context triple: [Hanbury Brown and Twiss effect, measurementMethod, correlation of intensity fluctuations at two detectors]
  • A. hasMeasurement
    Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
  • B. assessmentMethod
    Indicates the method or procedure used to evaluate, measure, or judge something.
  • C. method chosen
    Indicates the technique, procedure, or process used by an entity to perform an action or achieve a result.
  • D. measuredFrom
    Indicates that a measurement or value is determined relative to, or using, a specified reference point or source.
  • E. hasMeasurementDifficulty
    Indicates that performing a measurement on something is challenging or problematic in some way.
  • 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_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efbed5b88190a45716812eb4cfdf completed Feb. 28, 2026, 1:38 p.m.
PD Predicate disambiguation batch_69a2ede8eac081908dffade6a5e7950b completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.