Triple

T4163853
Position Surface form Disambiguated ID Type / Status
Subject false vacuum inflation E84393 entity
Predicate facesProblem P13650 FINISHED
Object inhomogeneous reheating due to bubble collisions in original model 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: inhomogeneous reheating due to bubble collisions in original model | Statement: [false vacuum inflation, facesProblem, inhomogeneous reheating due to bubble collisions in original model]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: facesProblem
Context triple: [false vacuum inflation, facesProblem, inhomogeneous reheating due to bubble collisions in original model]
  • A. faceType
    Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
  • B. facesChallenge
    Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
  • C. facingIssue chosen
    Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
  • D. faceValueType
    Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
  • E. facesBuilding
    Indicates that one building is oriented toward and directly faces another building.
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0321eee88190871c1d4bf44a5007 completed March 9, 2026, 5:28 p.m.
PD Predicate disambiguation batch_69af018dc90c8190a754b1bfbc802e80 completed March 9, 2026, 5:21 p.m.
Created at: March 9, 2026, 3:44 p.m.