Triple
T9547097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nujiang |
E230319
|
entity |
| Predicate | provinceLevel |
P67341
|
FINISHED |
| Object | prefecture-level division |
—
|
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: prefecture-level division | Statement: [Nujiang, provinceLevel, prefecture-level division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: provinceLevel Context triple: [Nujiang, provinceLevel, prefecture-level division]
-
A.
hasProvinceLevelUnit
Indicates that one administrative or territorial entity possesses or contains a sub-unit at the province (or equivalent) level.
-
B.
provinceType
chosen
Indicates the classification or category of a province, specifying what type of administrative or territorial unit it is.
-
C.
provinceName
Indicates that a province entity is associated with its specific name as a textual label.
-
D.
province
Indicates that one entity is an administrative subdivision or region (a province) governed by or belonging to another, typically larger, political or territorial entity.
-
E.
mainProvinces
Indicates that certain provinces are the primary or most significant administrative regions associated with a given entity.
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9902fca081909125660ae6336d3f |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:02 p.m.