Triple
T37423527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeremy Bamber |
E929925
|
entity |
| Predicate | crimeScene |
P188065
|
FINISHED |
| Object | White House Farm |
—
|
NE NERFINISHED |
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: White House Farm | Statement: [Jeremy Bamber, crimeScene, White House Farm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crimeScene Context triple: [Jeremy Bamber, crimeScene, White House Farm]
-
A.
crimeAgainst
Indicates that one entity commits or is responsible for a criminal act directed toward another entity.
-
B.
hasCrimeScene
Indicates that a particular location or setting is the site where a specific crime occurred or was discovered.
-
C.
featuresMurderInvestigation
Indicates that the subject involves or includes a murder investigation as a central element or storyline.
-
D.
murderedIn
Indicates that one entity unlawfully killed another entity at or within a specified location.
-
E.
methodOfMurderScheme
Indicates the specific method or scheme by which a murder is carried out in a given situation or plan.
- F. None of above. chosen
Provenance (4 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_69f76ebf0f288190ba198a78341613b8 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69fb9e173f348190b7ab5935e4dca039 |
completed | May 6, 2026, 8:01 p.m. |
Created at: May 3, 2026, 4:16 p.m.