Triple
T29604021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mare de Déu de la Mercè |
E754527
|
entity |
| Predicate | hasTitleInCatalan |
P15390
|
FINISHED |
| Object | Mare de Déu de la Mercè |
—
|
NE NERFINISHED |
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: Mare de Déu de la Mercè | Statement: [Mare de Déu de la Mercè, hasTitleInCatalan, Mare de Déu de la Mercè]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInCatalan Context triple: [Mare de Déu de la Mercè, hasTitleInCatalan, Mare de Déu de la Mercè]
-
A.
hasNameInCatalan
Indicates that an entity is associated with a specific name expressed in the Catalan language.
-
B.
titleInSpanish
Indicates that one entity is the title of another entity expressed in the Spanish language.
-
C.
hasLatinTitleOf
Indicates that one entity has, uses, or is associated with the Latin-language title corresponding to another entity.
-
D.
hasTitleInEsperanto
Indicates that an entity has a specific title expressed in the Esperanto language.
-
E.
hasTitleInLanguage
chosen
Indicates that an entity has a specific title expressed in a particular language.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: April 28, 2026, 6:24 p.m.