Triple
T31508840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muse |
E803888
|
entity |
| Predicate | provinceLevelNeighborInChina |
P62207
|
FINISHED |
| Object | Dehong Dai and Jingpo Autonomous Prefecture |
—
|
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: Dehong Dai and Jingpo Autonomous Prefecture | Statement: [Muse, provinceLevelNeighborInChina, Dehong Dai and Jingpo Autonomous Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: provinceLevelNeighborInChina Context triple: [Muse, provinceLevelNeighborInChina, Dehong Dai and Jingpo Autonomous Prefecture]
-
A.
nearbyCountryProvince
Indicates that a province is geographically close to, or shares a border with, a specified country.
-
B.
otherProvinceInChina
Indicates that two provinces are distinct from each other while both being located within China.
-
C.
adjacentProvince
chosen
Indicates that two provinces share a common boundary and are directly next to each other geographically.
-
D.
hasNearbyProvince
Indicates that one province is geographically close to or directly adjacent to another province.
-
E.
autonomousPrefectureInChina
Indicates that one administrative region is an autonomous prefecture located within the territorial jurisdiction of China.
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: April 30, 2026, 9:48 p.m.