Triple
T29786907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chou (Wade–Giles) |
E756288
|
entity |
| Predicate | mapsToModernStandard |
P158739
|
FINISHED |
| Object | Zhou (Hanyu Pinyin) |
—
|
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: Zhou (Hanyu Pinyin) | Statement: [Chou (Wade–Giles), mapsToModernStandard, Zhou (Hanyu Pinyin)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mapsToModernStandard Context triple: [Chou (Wade–Giles), mapsToModernStandard, Zhou (Hanyu Pinyin)]
-
A.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
-
B.
hasModernStandardForms
chosen
Indicates that an entity possesses one or more contemporary, standardized versions or representations of itself.
-
C.
romanizationStandardReplacedBy
Indicates that one system or convention for romanization has been superseded and replaced by another romanization standard.
-
D.
isModernFormOf
Indicates that one entity is a newer or contemporary version, adaptation, or evolution of another earlier entity.
-
E.
standardTransliteration
Indicates that one representation of text is a transliteration of another according to a recognized standard or convention.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f674abd4bc81908993a7677238b80c |
completed | May 2, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:09 p.m.