Triple
T24070433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | murder of Albert Snyder |
E596209
|
entity |
| Predicate | hasStagedSceneAs |
P154748
|
FINISHED |
| Object | burglary |
—
|
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: burglary | Statement: [murder of Albert Snyder, hasStagedSceneAs, burglary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStagedSceneAs Context triple: [murder of Albert Snyder, hasStagedSceneAs, burglary]
-
A.
containsScene
Indicates that one entity (typically a media item or narrative work) includes or features a particular scene as part of its content.
-
B.
hasStageIn
Indicates a relationship where one entity occurs, exists, or takes place within a particular stage or phase of another process, lifecycle, or sequence.
-
C.
hasLastSceneWith
Indicates that two entities share the same final scene or appearance together within a work or sequence.
-
D.
hasCheckpointScene
Indicates that an event, process, or narrative includes a specific checkpoint scene or moment where progress is marked or evaluated.
-
E.
stagedIn
Indicates that an event, performance, or production takes place or is set within a particular location or venue.
- 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db17c99881909f97e858fb183d86 |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:41 p.m.