Triple

T11876351
Position Surface form Disambiguated ID Type / Status
Subject Blunder Bowl E282535 entity
Predicate associatedWithNotableError P60124 FINISHED
Object multiple interceptions 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: multiple interceptions | Statement: [Blunder Bowl, associatedWithNotableError, multiple interceptions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithNotableError
Context triple: [Blunder Bowl, associatedWithNotableError, multiple interceptions]
  • A. notableException
    Indicates that something or someone stands out as an unusual or noteworthy deviation from an expected pattern, rule, or general case.
  • B. hasNotableIssue
    Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
  • C. associatedFault chosen
    Indicates a relationship where a given entity is linked to, or occurs in connection with, a specific fault or error condition.
  • D. notableExceptionArea
    Indicates that a specific area is recognized as an exception to a general rule, pattern, or classification that applies elsewhere.
  • E. notableEarlyIssue
    Indicates that the subject is a significant or noteworthy early edition, release, or version of the object.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d39d2934819093b9f7006f45e5cb completed April 10, 2026, 10:40 a.m.
PD Predicate disambiguation batch_69d8bb272f88819090c37c944c5a60ab completed April 10, 2026, 8:56 a.m.
Created at: April 8, 2026, 9:44 p.m.