Triple
T37843998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Orlofsky |
E943552
|
entity |
| Predicate | relationshipToFalke |
P204422
|
FINISHED |
| Object | accomplice in practical joke |
—
|
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: accomplice in practical joke | Statement: [Prince Orlofsky, relationshipToFalke, accomplice in practical joke]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToFalke Context triple: [Prince Orlofsky, relationshipToFalke, accomplice in practical joke]
-
A.
relationshipToFelix
Indicates the specific type of relationship or connection that an entity has with Felix.
-
B.
relationshipToFranKubelik
Indicates the specific type of personal or social relationship an entity has with Fran Kubelik.
-
C.
topFlightRelationship
Indicates a relationship where one entity is the primary or most important flight associated with another entity, such as a top-ranked, preferred, or main flight option.
-
D.
opusRelationship
Indicates a relationship between creative works (opuses), such as versions, adaptations, or parts within a larger compositional whole.
-
E.
isFlankerOf
Indicates that one entity occupies or performs the role of a flanker in relation to another entity, typically providing support or coverage from the side.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:19 p.m.