Triple

T9781898
Position Surface form Disambiguated ID Type / Status
Subject Angelus E237394 entity
Predicate timeMarkerFunction P43062 FINISHED
Object marks hours of the day 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: marks hours of the day | Statement: [Angelus, timeMarkerFunction, marks hours of the day]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeMarkerFunction
Context triple: [Angelus, timeMarkerFunction, marks hours of the day]
  • A. timeIndexed
    Indicates that the relationship or property it connects is associated with, or valid during, a specific time or time interval.
  • B. timeShiftProperty
    Indicates a relationship where one property value is derived from another by applying a temporal shift (e.g., offsetting it to an earlier or later point in time).
  • C. timeInSeries
    Indicates that one temporal value occurs within the duration or sequence span defined by another in a series.
  • D. timeNamed chosen
    Indicates that a specific time or temporal interval is referred to or identified by a particular name or label.
  • E. timeScaleType
    Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
  • 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_69ca84da927881909bda80caecad6010 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda1b23cb88190b458ab18d5f7f493 completed April 1, 2026, 10:52 p.m.
PD Predicate disambiguation batch_69cd03d77c6c81909b675955bf113320 completed April 1, 2026, 11:39 a.m.
Created at: March 30, 2026, 8:27 p.m.