Triple
T33569724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 长寿路 |
E859860
|
entity |
| Predicate | 是否有周边商住街区 |
P174428
|
FINISHED |
| Object | 是 |
—
|
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: 是 | Statement: [长寿路, 是否有周边商住街区, 是]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 是否有周边商住街区 Context triple: [长寿路, 是否有周边商住街区, 是]
-
A.
connectsToCommercialArea
Indicates that one location has a direct link, route, or access path to a commercial area.
-
B.
isResidentialAreaForCommutersTo
Indicates that a residential area primarily houses people who commute to the specified destination for work or other regular activities.
-
C.
isKeyCommercialAndResidentialArea
chosen
Indicates that a location serves as a major hub for both commercial activities and residential living.
-
D.
hasNoCommercialZone
Indicates that the subject area or entity does not contain any designated commercial zone or commercial-use area.
-
E.
hasWalkableNeighborhoods
Indicates that the subject is associated with neighborhoods where people can conveniently and safely walk to destinations such as homes, shops, services, or public spaces.
- 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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f742f9788190be2d5890a46bfe8b |
completed | May 3, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.