Triple

T8640839
Position Surface form Disambiguated ID Type / Status
Subject Erdős–Rényi model E204641 entity
Predicate probabilitySpace P51618 FINISHED
Object set of all simple graphs on n labeled vertices 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: set of all simple graphs on n labeled vertices | Statement: [Erdős–Rényi model, probabilitySpace, set of all simple graphs on n labeled vertices]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: probabilitySpace
Context triple: [Erdős–Rényi model, probabilitySpace, set of all simple graphs on n labeled vertices]
  • A. definesProbability
    Indicates that one entity specifies or assigns the probability value associated with another entity or event.
  • B. holdsAlmostSurely
    Indicates that the specified property or event occurs with probability 1, i.e., it is true almost everywhere except possibly on a set of outcomes of probability zero.
  • C. seedSpace
    Indicates a relationship where an entity provides or occupies an initial area, context, or capacity from which growth, development, or further allocation can begin.
  • D. typicalStateSpace chosen
    Indicates the usual or standard set of states in which an entity, system, or process is considered to operate.
  • E. stochastic
    Indicates that the relationship or process involves randomness or probabilistic behavior rather than being fully deterministic.
  • 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_69ca834ca1c88190a11ffb0200342fac completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc47944d1c819081f448f14d04bf9d completed March 31, 2026, 10:15 p.m.
PD Predicate disambiguation batch_69cc455d6d448190a2da2a319ac78c37 completed March 31, 2026, 10:06 p.m.
Created at: March 30, 2026, 6:28 p.m.