Triple
T16649096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Age detective fiction |
E404554
|
entity |
| Predicate | hasTypicalCrime |
P7957
|
FINISHED |
| Object | murder |
—
|
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: murder | Statement: [Golden Age detective fiction, hasTypicalCrime, murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCrime Context triple: [Golden Age detective fiction, hasTypicalCrime, murder]
-
A.
hasCrimeElement
Indicates that a situation, action, or entity involves or contains a component that is legally recognized as part of a crime.
-
B.
crimeRate
Indicates the frequency or level of criminal activity occurring within a given area or population.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
hasCrimeGroup
Indicates a relationship where an entity is associated with, belongs to, or is controlled by a particular criminal group or organization.
-
E.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad794388190b2817d2ec5ff0de0 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.