Triple
T28543763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa de los Pocillos |
E722370
|
entity |
| Predicate | hasCleanliness |
P146343
|
FINISHED |
| Object | regularly maintained |
—
|
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: regularly maintained | Statement: [Playa de los Pocillos, hasCleanliness, regularly maintained]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCleanliness Context triple: [Playa de los Pocillos, hasCleanliness, regularly maintained]
-
A.
hasCleanlinessLevel
chosen
Indicates the degree or state of cleanliness associated with an entity.
-
B.
hasCleaningFacility
Indicates that an entity provides or is equipped with a facility or service for cleaning.
-
C.
notCleanedFor
Indicates that one entity has not been cleaned, maintained, or cleared in preparation for use by another entity.
-
D.
hasCleaningService
Indicates that an entity receives or is provided with a cleaning service from another entity.
-
E.
usesCleanContent
Indicates that one entity employs or relies on content that is free from inappropriate, offensive, or unsafe material.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.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. |
Created at: April 28, 2026, 3:37 a.m.