Triple
T15756074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casa de Campo metro station |
E381969
|
entity |
| Predicate | servesInterest |
P101736
|
FINISHED |
| Object | tourists visiting Casa de Campo |
—
|
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: tourists visiting Casa de Campo | Statement: [Casa de Campo metro station, servesInterest, tourists visiting Casa de Campo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesInterest Context triple: [Casa de Campo metro station, servesInterest, tourists visiting Casa de Campo]
-
A.
servesIntersection
Indicates that one entity provides service or operational coverage to a specific road or transit intersection.
-
B.
servesUse
Indicates that one entity is used by or functions to serve the purpose or needs of another entity.
-
C.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
D.
regulatesOrServes
Indicates that one entity controls, governs, or provides a service or function for another entity.
-
E.
providesServiceTowards
chosen
Indicates that one entity delivers or performs a service directed to or for the benefit of another entity.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.