Triple
T5665187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libro de Ordenanza de los toques militares de la Infantería Española |
E124841
|
entity |
| Predicate | tieneContenido |
P22683
|
FINISHED |
| Object | toques militares reglamentarios |
—
|
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: toques militares reglamentarios | Statement: [Libro de Ordenanza de los toques militares de la Infantería Española, tieneContenido, toques militares reglamentarios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneContenido Context triple: [Libro de Ordenanza de los toques militares de la Infantería Española, tieneContenido, toques militares reglamentarios]
-
A.
containedWith
Indicates that one entity is located or kept inside the bounds or interior space of another entity.
-
B.
hasContentFrom
chosen
Indicates that one entity’s content is derived from, includes, or is based on another entity.
-
C.
containsArticle
Indicates that one entity includes or holds an article (such as a written piece, item, or document) as part of its contents.
-
D.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
-
E.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:43 p.m.