Triple

T15803486
Position Surface form Disambiguated ID Type / Status
Subject Chiu E383152 entity
Predicate romanizationContext P120140 FINISHED
Object older romanization systems for Mandarin 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: older romanization systems for Mandarin | Statement: [Chiu, romanizationContext, older romanization systems for Mandarin]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: romanizationContext
Context triple: [Chiu, romanizationContext, older romanization systems for Mandarin]
  • A. romanizationOccurred
    Indicates that a process of converting text from one writing system into the Roman (Latin) alphabet has taken place.
  • B. romanizationProcess
    Indicates the process of converting text from a non-Latin writing system into a representation using the Latin alphabet.
  • C. romanizationOfToponymType
    Indicates a relationship where a specific type of place-name is expressed in a romanized (Latin-script) form corresponding to its original writing system.
  • D. romanizationBegan
    Indicates that the process of converting text from one writing system into its representation using the Roman (Latin) alphabet was initiated.
  • E. hasRomanizationOf
    Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
  • 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b524835c8190ae286b2562f07756 completed April 16, 2026, 10:08 a.m.
PD Predicate disambiguation batch_69e0053b847c8190945726c3ddac21cc completed April 15, 2026, 9:38 p.m.
PDg Predicate description generation batch_69e00e48d49c819081afccb02f9cf18b completed April 15, 2026, 10:16 p.m.
Created at: April 10, 2026, 4:48 a.m.