Triple
T15645587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhongxiao Fuxing |
E376167
|
entity |
| Predicate | nearbyDistrictType |
P85695
|
FINISHED |
| Object | commercial district |
—
|
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: commercial district | Statement: [Zhongxiao Fuxing, nearbyDistrictType, commercial district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyDistrictType Context triple: [Zhongxiao Fuxing, nearbyDistrictType, commercial district]
-
A.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
B.
cityDistrictType
Indicates the type or classification of a city district within an urban or administrative structure.
-
C.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
D.
nearbyRegionCharacterizedBy
chosen
Indicates that a region located nearby another entity is defined or distinguished by a particular characteristic, feature, or condition.
-
E.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.