Triple
T26902347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiànyè Qū |
E678065
|
entity |
| Predicate | romanizedNameOf |
P135924
|
FINISHED |
| Object | Jianye District |
—
|
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: Jianye District | Statement: [Jiànyè Qū, romanizedNameOf, Jianye District]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanizedNameOf Context triple: [Jiànyè Qū, romanizedNameOf, Jianye District]
-
A.
romanizationFrom
Indicates that one entity is a romanized representation derived from the script or writing system of another entity.
-
B.
nameFormInLatin
Indicates that an entity’s name is expressed or recorded in its Latin-language form.
-
C.
romanizationVariantOf
chosen
Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
-
D.
hasLatinizedName
Indicates that an entity is associated with a version of its name that has been converted into Latin form or spelling.
-
E.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 5:51 a.m.