Triple
T19787266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Arthur Tragg |
E475303
|
entity |
| Predicate | typicalFunctionInPlot |
P32087
|
FINISHED |
| Object | conducts official police investigation |
—
|
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: conducts official police investigation | Statement: [Lieutenant Arthur Tragg, typicalFunctionInPlot, conducts official police investigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFunctionInPlot Context triple: [Lieutenant Arthur Tragg, typicalFunctionInPlot, conducts official police investigation]
-
A.
typicalFunction
Indicates that something serves as the usual or characteristic function or role of an entity.
-
B.
hasFunctionInPlot
chosen
Indicates that an entity serves a particular role or purpose within the structure or progression of a plot.
-
C.
primaryFunctionInPlot
Indicates the main narrative role or purpose that an entity serves within the plot of a story.
-
D.
solutionInPlot
Indicates that a solution or answer is presented or revealed within the narrative structure or storyline of a plot.
-
E.
traditionalFunction
Indicates that an entity serves a customary or historically established role or purpose within a cultural or social 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65389145881909385f36f56cd250b |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.