Triple
T7723502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casa de Convalescència, Barcelona |
E175070
|
entity |
| Predicate | languageCommunityAssociated |
P5562
|
FINISHED |
| Object | Catalan language |
—
|
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: Catalan language | Statement: [Casa de Convalescència, Barcelona, languageCommunityAssociated, Catalan language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCommunityAssociated Context triple: [Casa de Convalescència, Barcelona, languageCommunityAssociated, Catalan language]
-
A.
hasLanguageCommunity
chosen
Indicates that an entity is associated with or serves a particular language community.
-
B.
languageLocalCommunities
Indicates that a language is used, maintained, or holds significance within specific local communities or regions.
-
C.
associatedCommunity
Indicates a relationship where an entity is linked or connected to a particular community with which it is involved or identified.
-
D.
languageFamilyAssociated
Indicates that there is an association or connection between a language and a particular language family.
-
E.
languageAssociation
Indicates an association or relationship between entities based on a language they use, represent, or are linked to.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.