Triple
T29190817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vinz |
E739983
|
entity |
| Predicate | fantasizesAbout |
P69553
|
FINISHED |
| Object | killing a police officer |
—
|
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: killing a police officer | Statement: [Vinz, fantasizesAbout, killing a police officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fantasizesAbout Context triple: [Vinz, fantasizesAbout, killing a police officer]
-
A.
dream
chosen
Indicates that an entity experiences or has a dream involving another entity or concept.
-
B.
hasFictionalGoal
Indicates that an entity is associated with a goal or objective that exists only within a fictional, imagined, or narrative context.
-
C.
hasDreamFrom
Indicates that an entity experiences or receives a dream that originates from another entity or source.
-
D.
fictionalSon
Indicates that one entity is portrayed as the son of another entity within a fictional or narrative context.
-
E.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6638aa68c8190a02fd50ecd5a96fd |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:02 p.m.