Triple
T37839689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuhan metropolitan transport network |
E943437
|
entity |
| Predicate | integratesCity |
P124077
|
FINISHED |
| Object | Ezhou |
—
|
NE NERFINISHED |
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: Ezhou | Statement: [Wuhan metropolitan transport network, integratesCity, Ezhou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: integratesCity Context triple: [Wuhan metropolitan transport network, integratesCity, Ezhou]
-
A.
integratedIntoCity
Indicates that something has been incorporated and functions as a part of a city’s overall structure, system, or environment.
-
B.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
C.
cityFunction
Indicates the primary role, purpose, or functional classification associated with a city (e.g., administrative, commercial, industrial, cultural).
-
D.
integratedIntoUrbanNetwork
chosen
Indicates that an entity has been incorporated into and functions as part of a broader urban infrastructure or service network.
-
E.
municipalIntegration
Indicates the incorporation or coordination of local governmental functions, services, or jurisdictions into a unified municipal framework.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.