Triple
T7238822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hubert-Joseph Henry |
E155301
|
entity |
| Predicate | criminalAction |
P11256
|
FINISHED |
| Object | forgery of documents |
—
|
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: forgery of documents | Statement: [Hubert-Joseph Henry, criminalAction, forgery of documents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminalAction Context triple: [Hubert-Joseph Henry, criminalAction, forgery of documents]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
committedCrime
chosen
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
C.
crimeListedInArticleIII
Indicates that a particular crime is one of the offenses expressly mentioned in Article III of the relevant constitution or legal document.
-
D.
criminalOrganization
Indicates that the subject is an organized group engaged in ongoing illegal activities, often with structured hierarchy and coordination.
-
E.
recognitionOfCrimes
Indicates the formal acknowledgment or identification that certain actions or events constitute crimes under a legal or normative framework.
- 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_69c688143bfc81908d4176617735e601 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea552a688190a00f5d0ad982f787 |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:55 p.m.