Triple
T12520607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montjuïc Cable Car |
E299303
|
entity |
| Predicate | hasStationAt |
P105426
|
FINISHED |
| Object | lower station on Montjuïc hill |
—
|
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: lower station on Montjuïc hill | Statement: [Montjuïc Cable Car, hasStationAt, lower station on Montjuïc hill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationAt Context triple: [Montjuïc Cable Car, hasStationAt, lower station on Montjuïc hill]
-
A.
hasStationNear
Indicates that one entity has a station located in close proximity to another entity.
-
B.
hasStationInCity
Indicates that a station or facility is located within a particular city.
-
C.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
-
D.
hasStationFunction
Indicates that an entity serves in a particular functional role or capacity at a station.
-
E.
hasStationAtAirport
Indicates that an organization or service operates a station or facility located at a specific airport.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954b715fc819091fa84430be46273 |
completed | April 10, 2026, 7:51 p.m. |
Created at: April 8, 2026, 9:57 p.m.