Triple
T6959223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franchise Pictures |
E161324
|
entity |
| Predicate | consequenceOfLegalIssues |
P4511
|
FINISHED |
| Object | filed for bankruptcy |
—
|
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: filed for bankruptcy | Statement: [Franchise Pictures, consequenceOfLegalIssues, filed for bankruptcy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceOfLegalIssues Context triple: [Franchise Pictures, consequenceOfLegalIssues, filed for bankruptcy]
-
A.
violationConsequences
Indicates the negative outcomes, penalties, or repercussions that result from a violation of a rule, law, or agreement.
-
B.
hasLegalIssue
chosen
Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
-
C.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
-
D.
consequenceOfRevocation
Indicates that something occurs as a direct result of a prior revocation event or decision.
-
E.
causeOfLegalCondemnation
Indicates that one entity is the reason or basis for another entity being legally condemned, judged guilty, or subjected to legal penalties.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daedbb4c8190b46846fb1265b937 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:29 p.m.