Triple
T38170273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ley de reforma a la Ley General de Cultura |
E1000052
|
entity |
| Predicate | modifica |
P43320
|
FINISHED |
| Object | Ley General de Cultura |
—
|
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: Ley General de Cultura | Statement: [Ley de reforma a la Ley General de Cultura, modifica, Ley General de Cultura]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modifica Context triple: [Ley de reforma a la Ley General de Cultura, modifica, Ley General de Cultura]
-
A.
modification
chosen
Indicates a change made to an existing entity, altering its properties, structure, or state from a prior version.
-
B.
modificationBy
Indicates that one entity has been altered, changed, or adjusted as a result of an action performed by another entity.
-
C.
laterModification
Indicates that one entity is a modification or revision that occurs after another in time.
-
D.
amendedFor
Indicates that one entity has been modified or revised specifically to address, correct, or accommodate another entity.
-
E.
modulates
Indicates that one entity adjusts, regulates, or alters the intensity, frequency, or effect of another entity or process.
- 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_69f76daaace48190a38cee37f8ce343f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:29 p.m.