Triple

T28948148
Position Surface form Disambiguated ID Type / Status
Subject 稲城市 E730934 entity
Predicate 時間帯 P302 FINISHED
Object 日本標準時 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: 日本標準時 | Statement: [稲城市, 時間帯, 日本標準時]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: 時間帯
Context triple: [稲城市, 時間帯, 日本標準時]
  • A. timePeriod chosen
    Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
  • B. time
    Indicates a temporal relationship specifying when an event occurs or how entities are ordered or related in time.
  • C. timePeriodFormulated
    Indicates the time period during which something (such as a concept, theory, or plan) was formulated or developed.
  • D. timePeriodQualifier
    Indicates how a time-related statement or value is further specified or constrained, such as by defining its scope, phase, or contextual condition within a broader time period.
  • E. timeType
    Indicates the specific temporal category or classification associated with a time-related entity or value (e.g., duration, point in time, interval, or recurrence type).
  • 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_69f043eb9bcc819091ac7b07aecb6475 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f65b8a9a6c819091b9ec4563704490 completed May 2, 2026, 8:16 p.m.
PD Predicate disambiguation batch_69f659d02f1c8190831758ac52bb54e4 completed May 2, 2026, 8:08 p.m.
Created at: April 28, 2026, 8:42 a.m.