Triple
T37640115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revised Penal Code of the Philippines |
E936592
|
entity |
| Predicate | RA10951Effect |
P188554
|
FINISHED |
| Object | adjusted fines and penalties |
—
|
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: adjusted fines and penalties | Statement: [Revised Penal Code of the Philippines, RA10951Effect, adjusted fines and penalties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RA10951Effect Context triple: [Revised Penal Code of the Philippines, RA10951Effect, adjusted fines and penalties]
-
A.
section10Effect
Indicates the legal consequences or impact that arise specifically from the application or enforcement of Section 10 of a statute or agreement.
-
B.
attackEffect
Indicates that one entity’s attack produces a specific effect or consequence on another entity.
-
C.
defeatEffect
Indicates that one entity’s defeat causes a particular outcome or change to occur for another entity or the overall situation.
-
D.
tailAttackEffect
Indicates an effect that occurs when an entity performs an attack using its tail.
-
E.
providesEffect
Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
- F. None of above. chosen
Provenance (4 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_69f76ed31d8881908405da6c6d2f0463 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa19e4a88190b04f26c0d4e708fd |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbaa108ee48190b84d13df3ef3e365 |
completed | May 6, 2026, 8:52 p.m. |
Created at: May 3, 2026, 4:18 p.m.