Triple
T24675620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alta Ribagorça |
E610975
|
entity |
| Predicate | hasReligiousArchitectureStyle |
P69416
|
FINISHED |
| Object | Romanesque |
—
|
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: Romanesque | Statement: [Alta Ribagorça, hasReligiousArchitectureStyle, Romanesque]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousArchitectureStyle Context triple: [Alta Ribagorça, hasReligiousArchitectureStyle, Romanesque]
-
A.
hasReligiousBuildingStyle
chosen
Indicates that one entity (typically a building) exhibits or is characterized by the architectural style associated with a particular religion or religious tradition.
-
B.
hasCathedralStyle
Indicates that something possesses or is characterized by a particular architectural style associated with a cathedral.
-
C.
hasReligiousBuildingAlong
Indicates that a religious building is located along the course, path, or extent of the referenced entity.
-
D.
hasReligiousInstitutionType
Indicates that an entity is associated with, or classified by, a specific type of religious institution.
-
E.
notableMosqueArchitectureStyle
Indicates that a mosque is characterized by or exemplifies a particular architectural style.
- 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_69e2c4d5c2dc8190ac857dea25ec6ce9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 3:04 a.m.