Triple
T282538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gag Law (Ley de la Mordaza) |
E5820
|
entity |
| Predicate | criminalized |
P4539
|
FINISHED |
| Object | pro-independence expression |
—
|
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: pro-independence expression | Statement: [Gag Law (Ley de la Mordaza), criminalized, pro-independence expression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminalized Context triple: [Gag Law (Ley de la Mordaza), criminalized, pro-independence expression]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
prosecuted
Indicates that legal authorities have formally brought criminal charges against an entity and pursued a case against them in a court of law.
-
C.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
D.
criminalStatus
Indicates the legal condition of an entity with respect to criminal law, such as whether they are accused, convicted, or cleared of a crime.
-
E.
useCriminalizedUnderGagLaw
chosen
Indicates that the act of using something is treated as a criminal offense under a specific gag law or speech-restricting legal provision.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e0c14b48190a5c936bab36180b3 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b77e028819087e606fc321219f7 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.