Triple
T15187089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cliff Lewis |
E362904
|
entity |
| Predicate | hasRelationshipTypeWithJimmyPorter |
P117047
|
FINISHED |
| Object | friendship |
—
|
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: friendship | Statement: [Cliff Lewis, hasRelationshipTypeWithJimmyPorter, friendship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithJimmyPorter Context triple: [Cliff Lewis, hasRelationshipTypeWithJimmyPorter, friendship]
-
A.
relationshipTypeWithBertieWooster
Indicates the specific nature or category of relationship an entity has with Bertie Wooster.
-
B.
hasRelationshipTypeWith Vince Tyler
Indicates that an entity is connected to Vince Tyler by a specific, characterized type of relationship.
-
C.
relationshipTypeWithNinaSayers
Indicates the specific nature or category of relationship that an entity has with Nina Sayers.
-
D.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
E.
relationshipToBertieWooster
Indicates the specific type of personal or social relationship an entity has with Bertie Wooster.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec72059c08190a34f513a00185b08 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:09 a.m.