Triple
T29798876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1981 Wonderland Avenue murders |
E756632
|
entity |
| Predicate | crimeSceneType |
P84849
|
FINISHED |
| Object | private residence |
—
|
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: private residence | Statement: [1981 Wonderland Avenue murders, crimeSceneType, private residence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crimeSceneType Context triple: [1981 Wonderland Avenue murders, crimeSceneType, private residence]
-
A.
featuresMurderInvestigation
Indicates that the subject involves or includes a murder investigation as a central element or storyline.
-
B.
crimeLocation
Indicates that a crime occurred at, or is associated with, a particular location.
-
C.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
D.
settingOfCrime
chosen
Indicates the location or environment in which a crime takes place.
-
E.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another 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_69f22454583081908927516cb9938d1d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f674e861f08190a85ab46799e50c74 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 5:17 p.m.