Triple

T21868646
Position Surface form Disambiguated ID Type / Status
Subject Sidney Lau Cantonese romanization E539946 entity
Predicate toneCount P145982 FINISHED
Object 9 (including entering tones) 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: 9 (including entering tones) | Statement: [Sidney Lau Cantonese romanization, toneCount, 9 (including entering tones)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: toneCount
Context triple: [Sidney Lau Cantonese romanization, toneCount, 9 (including entering tones)]
  • A. inTonality
    Indicates that something (such as a musical element, passage, or piece) is expressed, structured, or interpreted within a specific musical key or tonal framework.
  • B. tonal
    Indicates that one entity has a tone, pitch pattern, or tonal quality in relation to another (such as a language, sound, or musical element).
  • C. tonalSystem
    Indicates a relationship where a language or musical system is characterized by a specific set of tonal patterns or pitch distinctions that structure its sounds or expressions.
  • D. tone
    Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
  • E. marksTones
    Indicates that one entity applies or denotes tonal markings or distinctions on another entity, such as in language or notation.
  • F. None of above. chosen

Provenance (4 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_69e0c478f59081909d54302b57fc1ce3 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0f33305d081908cd070134420607a completed April 28, 2026, 5:49 p.m.
PD Predicate disambiguation batch_69e6be9394f88190945ddd1dc004d29d completed April 21, 2026, 12:02 a.m.
PDg Predicate description generation batch_69e6d054737081908aa7112975b77475 completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 6:57 p.m.