Triple
T25117116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa de Melenara |
E629157
|
entity |
| Predicate | hasRescueService |
P464
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Playa de Melenara, hasRescueService, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRescueService Context triple: [Playa de Melenara, hasRescueService, yes]
-
A.
hasFireRescueService
Indicates that an entity is served by, or responsible for providing, a fire and rescue service.
-
B.
hasEmergencyServices
chosen
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
C.
hasEmergencyServiceProvider
Indicates that an entity is associated with or served by a specific emergency service provider (such as police, fire, or medical services).
-
D.
hasSupportService
Indicates that one entity provides or is associated with a support-related service for another entity.
-
E.
hasFireAndRescueServiceCategory
Indicates the specific fire and rescue service classification or category assigned to an entity, such as a building, facility, or site.
- 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_69e2ff3169d08190973b6061d5009abd |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 18, 2026, 6:27 a.m.