Triple
T171204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin "Bugsy" Siegel |
E3124
|
entity |
| Predicate | criminalStatus |
P7958
|
FINISHED |
| Object | deceased |
—
|
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: deceased | Statement: [Benjamin "Bugsy" Siegel, criminalStatus, deceased]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminalStatus Context triple: [Benjamin "Bugsy" Siegel, criminalStatus, deceased]
-
A.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
B.
crimeListedInArticleIII
Indicates that a particular crime is one of the offenses expressly mentioned in Article III of the relevant constitution or legal document.
-
C.
imprisonedFor
Indicates that one entity is held in detention or jail as a consequence of, or in connection with, a specific reason, action, or offense committed by another entity or itself.
-
D.
positionOnCrime
Indicates a stance, opinion, or policy position that an entity holds regarding crime or crime-related issues.
-
E.
prosecuted
Indicates that legal authorities have formally brought criminal charges against an entity and pursued a case against them in a court of law.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a25a3f9d188190aacf5791273e2c65 |
completed | Feb. 28, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69a25667717c8190bac5108366e2178d |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25a3ee6d08190a451ddba7504ce9b |
completed | Feb. 28, 2026, 3 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.