Triple
T37640093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revised Penal Code of the Philippines |
E936592
|
entity |
| Predicate | bookTwoCovers |
P108229
|
FINISHED |
| Object | specific crimes |
—
|
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: specific crimes | Statement: [Revised Penal Code of the Philippines, bookTwoCovers, specific crimes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookTwoCovers Context triple: [Revised Penal Code of the Philippines, bookTwoCovers, specific crimes]
-
A.
book4Covers
Indicates that one entity is the front or outer covering (such as a dust jacket or protective layer) of a book.
-
B.
book2Covers
chosen
Indicates that one entity (typically a book) has another entity as its cover or is associated with a specific cover representation.
-
C.
bookAppearance
Indicates that an entity’s visual or physical characteristics as presented in a book are being described or referenced.
-
D.
book1Contains
Indicates that one book includes, encloses, or has as part of its content another specified element or section.
-
E.
isCoverOf
Indicates that one entity functions as a protective or enclosing layer placed over another entity.
- 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_69f76ed31d8881908405da6c6d2f0463 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.