Triple
T22451302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keller factory |
E554996
|
entity |
| Predicate | involvesLegalIssue |
P4511
|
FINISHED |
| Object | war profiteering |
—
|
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: war profiteering | Statement: [Keller factory, involvesLegalIssue, war profiteering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesLegalIssue Context triple: [Keller factory, involvesLegalIssue, war profiteering]
-
A.
mainLegalIssue
Indicates the primary legal question or dispute that is central to a case or legal matter.
-
B.
hasLegalIssue
chosen
Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
-
C.
involvesIssue
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
-
D.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
-
E.
legalDocumentInvolvement
Indicates that an entity is involved with a legal document in some specified role (e.g., author, signer, subject, or recipient).
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4ba6a88190a0a79e2c20fa8c08 |
completed | April 29, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.