Triple
T3696944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanggu |
E78481
|
entity |
| Predicate | cityDistrictLevel |
P49445
|
FINISHED |
| Object | development zone |
—
|
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: development zone | Statement: [Guanggu, cityDistrictLevel, development zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityDistrictLevel Context triple: [Guanggu, cityDistrictLevel, development zone]
-
A.
cityDistrictType
Indicates the type or classification of a city district within an urban or administrative structure.
-
B.
targetCityDistrict
Indicates that one entity is a specific city district that serves as the target or destination in relation to another entity.
-
C.
cityLevel
Indicates the administrative or hierarchical rank of a city within a broader regional or national structure.
-
D.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
E.
regionOfCity
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc5115ad8819085ffa938de3943f4 |
completed | March 8, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69adb84dc5808190850aa6975cb09e27 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb903be308190a8f1925f99e67c68 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:26 p.m.