Triple
T8949096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chongqing Metro |
E213296
|
entity |
| Predicate | cityTypeServed |
P57766
|
FINISHED |
| Object | mountainous megacity |
—
|
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: mountainous megacity | Statement: [Chongqing Metro, cityTypeServed, mountainous megacity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityTypeServed Context triple: [Chongqing Metro, cityTypeServed, mountainous megacity]
-
A.
cityServedType
chosen
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
-
B.
cityServedRegion
Indicates that a city provides services to, or functions as an administrative or economic center for, a specified region.
-
C.
alternativeCityServed
Indicates that one city functions as an alternative service location for another city, typically in contexts like transportation or logistics.
-
D.
nearbyCityServed
Indicates that a city is geographically close enough to another city to be considered within its service or support area.
-
E.
servedCity
Indicates that a service, route, or facility operates in, reaches, or is available to a particular city.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6709c7a48190ab503083a1d6a29f |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:59 p.m.