Triple
T29069197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Criminal |
E735765
|
entity |
| Predicate | typicalSettingForUse |
P37480
|
FINISHED |
| Object | parties |
—
|
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: parties | Statement: [Criminal, typicalSettingForUse, parties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSettingForUse Context triple: [Criminal, typicalSettingForUse, parties]
-
A.
typicalSettingConsumed
Indicates the usual context or environment in which something is normally consumed.
-
B.
typicalUseLocation
Indicates the usual or most common location where an entity is used or operates.
-
C.
usedAsSettingFor
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
D.
typicalCircumstance
Indicates the usual or commonly occurring situation, condition, or context in which an event, action, or relationship typically takes place.
-
E.
hasTypicalUseContext
chosen
Indicates that something is commonly or characteristically used within a particular situation, setting, or context.
- 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a016b2629c48190befb10581560d58f |
completed | May 11, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0167d5a2088190a68dbd2b87f73e80 |
completed | May 11, 2026, 5:23 a.m. |
Created at: April 28, 2026, 10:19 a.m.