Triple
T28478126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walsh investigation |
E720615
|
entity |
| Predicate | typeOfOffensesInvestigated |
P180198
|
FINISHED |
| Object | conspiracy |
—
|
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: conspiracy | Statement: [Walsh investigation, typeOfOffensesInvestigated, conspiracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOffensesInvestigated Context triple: [Walsh investigation, typeOfOffensesInvestigated, conspiracy]
-
A.
typeOfOffenseAddressed
chosen
Indicates the specific category or kind of offense that a given action, measure, or legal provision is intended to address.
-
B.
hasCrimeInvestigation
Indicates that an entity is the subject of, or associated with, a formal investigation into a crime.
-
C.
includesOffenseType
Indicates that one entity contains, specifies, or is associated with a particular category or type of offense.
-
D.
targetOffenderType
Indicates the specific category or type of offender that an action, rule, or condition is directed toward.
-
E.
handledCrimes
Indicates that an entity (such as a person or organization) took responsibility for dealing with, investigating, or managing specific crimes.
- 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_69f01a5983f48190b7c1b8857245a4f7 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
Created at: April 28, 2026, 2:53 a.m.