Triple
T11879599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Refugio de la Renclusa |
E282620
|
entity |
| Predicate | hasWinterRoom |
P5521
|
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: [Refugio de la Renclusa, hasWinterRoom, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinterRoom Context triple: [Refugio de la Renclusa, hasWinterRoom, yes]
-
A.
requiresEquipmentInWinter
Indicates that performing the related activity or fulfilling the related condition necessitates the use of specific equipment during winter.
-
B.
hasLongWinterSeason
Indicates that the referenced entity experiences a winter season that lasts for an extended or unusually long period of time.
-
C.
hasIndoorType
Indicates that an entity is associated with a specific type or category of indoor environment or indoor feature.
-
D.
hasRoom
chosen
Indicates that an entity possesses, contains, or is associated with a specific room.
-
E.
hasHeating
Indicates that an entity is equipped with or provides a heating system or heating capability.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.