Triple
T37036484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chow Chi-yuen |
E916651
|
entity |
| Predicate | hasNameInChineseRomanization |
P164578
|
FINISHED |
| Object | Chow Chi-yuen |
—
|
NE NERFINISHED |
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: Chow Chi-yuen | Statement: [Chow Chi-yuen, hasNameInChineseRomanization, Chow Chi-yuen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInChineseRomanization Context triple: [Chow Chi-yuen, hasNameInChineseRomanization, Chow Chi-yuen]
-
A.
hasChineseNameComponent
Indicates that an entity’s Chinese name includes a specific component, such as a particular character, syllable, or segment.
-
B.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
-
C.
hasChineseNameType
Indicates that an entity’s Chinese name belongs to a particular type or category (e.g., formal, short, transliterated).
-
D.
nameInLanguageRomanization
chosen
Indicates that an entity’s name is represented in the romanized (Latin-script) form of a particular language.
-
E.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
- 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_69f76e93ec4c8190be81cf87354d9155 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff90b673248190b4dda9e005642d17 |
completed | May 9, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69ff8d5bee1081909274052945e98a6f |
completed | May 9, 2026, 7:39 p.m. |
Created at: May 3, 2026, 4:14 p.m.