Triple
T8280519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lot |
E193657
|
entity |
| Predicate | peopleAccusedOf |
P9856
|
FINISHED |
| Object | sexualImmorality |
—
|
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: sexualImmorality | Statement: [Lot, peopleAccusedOf, sexualImmorality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peopleAccusedOf Context triple: [Lot, peopleAccusedOf, sexualImmorality]
-
A.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
B.
coAccusedInCaseWith
Indicates that two or more entities are jointly accused as defendants in the same legal case.
-
C.
accusedIn
Indicates that a person or entity is formally charged with wrongdoing in a particular case, proceeding, or context.
-
D.
accusedOf
chosen
Indicates that one entity has formally alleged or claimed that another entity committed a specific wrongdoing or offense.
-
E.
convictedIndividual
Indicates that an individual has been found guilty of a crime or offense through a formal legal process and has received a conviction.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb79ee66e48190af7058b14f3daac9 |
completed | March 31, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:51 p.m.