Triple
T33836988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 安定门 |
E867258
|
entity |
| Predicate | 在城市空间结构中的地位 |
P24665
|
FINISHED |
| Object | 北京中轴线北段附近重要节点 |
—
|
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: 北京中轴线北段附近重要节点 | Statement: [安定门, 在城市空间结构中的地位, 北京中轴线北段附近重要节点]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 在城市空间结构中的地位 Context triple: [安定门, 在城市空间结构中的地位, 北京中轴线北段附近重要节点]
-
A.
partOfUrbanLayout
Indicates that one entity is a component or constituent element within the overall structure or organization of an urban area.
-
B.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
C.
integratedIntoUrbanNetwork
Indicates that an entity has been incorporated into and functions as part of a broader urban infrastructure or service network.
-
D.
urbanHierarchy
Indicates a hierarchical relationship among urban areas, such as cities or towns, where one is ranked or positioned above or below another in an urban system.
-
E.
urbanPlanningFunction
chosen
Indicates a functional role or purpose that something serves within the planning, organization, or management of urban spaces and infrastructure.
- 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_69f34992ad40819087760ed939bd2a7a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7002f38308190af948b97a35a5b09 |
completed | May 3, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.