Triple
T21942454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ba Don Town |
E541854
|
entity |
| Predicate | isProvincialSubordinateTown |
P146632
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ba Don Town, isProvincialSubordinateTown, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isProvincialSubordinateTown Context triple: [Ba Don Town, isProvincialSubordinateTown, true]
-
A.
isSubProvincialCity
Indicates that a city holds a sub-provincial administrative status, ranking below a province but above ordinary prefecture-level cities in the governmental hierarchy.
-
B.
isProvincialLevelMunicipality
Indicates that a municipality holds the administrative status and authority of a province-level jurisdiction within a country’s governmental hierarchy.
-
C.
isPrefecture
Indicates that one entity functions as an administrative prefecture governing or representing the other entity.
-
D.
hasPrefecturalOffice
Indicates that a given location or administrative unit contains or hosts an official prefectural government office.
-
E.
subprefecture
Indicates that an entity is a subprefecture (an administrative subdivision) of another administrative region or jurisdiction.
- F. None of above. chosen
Provenance (4 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242345dc8190aa6ddf61cf864e2d |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb6991948190a428c3c3bfd1c3b8 |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:56 p.m.