Triple
T15527467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rueda |
E369118
|
entity |
| Predicate | hasDenominationNameOrigin |
P3325
|
FINISHED |
| Object | town of Rueda |
—
|
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: town of Rueda | Statement: [Rueda, hasDenominationNameOrigin, town of Rueda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDenominationNameOrigin Context triple: [Rueda, hasDenominationNameOrigin, town of Rueda]
-
A.
originatedInDenomination
Indicates that an entity began or was founded within a particular religious denomination.
-
B.
hasNameOrigin
chosen
Indicates that the origin or source of an entity’s name is specified by the related entity.
-
C.
denominationName
Indicates the specific religious or organizational denomination to which an entity belongs or is associated.
-
D.
denominationOfOrigin
Indicates a legally recognized origin relationship where a product’s quality or characteristics are specifically attributable to being produced in a particular geographic region.
-
E.
hasNameOriginType
Indicates that there is a specific type or category describing the origin of an entity’s name.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0414620588190958ffde651ccab5f |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 4:05 a.m.