Triple
T33998173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FGC urban rail system |
E871732
|
entity |
| Predicate | otherCitiesServed |
P180286
|
FINISHED |
| Object | Sant Cugat del Vallès |
—
|
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: Sant Cugat del Vallès | Statement: [FGC urban rail system, otherCitiesServed, Sant Cugat del Vallès]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherCitiesServed Context triple: [FGC urban rail system, otherCitiesServed, Sant Cugat del Vallès]
-
A.
associatedCityServed
Indicates that there is a relationship where a service, facility, or entity is linked to and serves a particular city.
-
B.
primaryCitiesServed
Indicates the main cities that are directly served or covered by a given entity’s services or operations.
-
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.
cityServedType
Indicates the type or category of city that is served by a given entity (such as a facility, service, or infrastructure).
- F. None of above. chosen
Provenance (4 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_69f3499f8cbc81908de6ec89fa91ea8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: May 1, 2026, 1:50 a.m.