Triple
T18264887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 汉江 |
E437456
|
entity |
| Predicate | 流域重要城市群 |
P33130
|
FINISHED |
| Object | 汉江流域城市群 |
—
|
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: 汉江流域城市群 | Statement: [汉江, 流域重要城市群, 汉江流域城市群]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 流域重要城市群 Context triple: [汉江, 流域重要城市群, 汉江流域城市群]
-
A.
majorUrbanCorridor
Indicates a primary transportation route that connects significant urban areas and supports major flows of people, goods, or services between them.
-
B.
hasMajorCityOnBasin
chosen
Indicates that a major city is located on or within the drainage basin of a specified water system.
-
C.
significantUrbanArea
Indicates that a location is classified as a major or important urban center within a broader geographic or administrative context.
-
D.
metropolitanAreaType
Indicates the classification of a metropolitan area according to its type or category (e.g., size, function, or administrative status).
-
E.
coversUrbanAreas
Indicates that something extends over, includes, or provides coverage for urban or metropolitan areas.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff79851481909a4bbeb14fb00647 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.