Triple
T32543770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Rockwell as Bob Fosse |
E831784
|
entity |
| Predicate | portraysRelationshipsWith |
P174335
|
FINISHED |
| Object | Gwen Verdon |
—
|
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: Gwen Verdon | Statement: [Sam Rockwell as Bob Fosse, portraysRelationshipsWith, Gwen Verdon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysRelationshipsWith Context triple: [Sam Rockwell as Bob Fosse, portraysRelationshipsWith, Gwen Verdon]
-
A.
portraysRelationshipWith
chosen
Indicates that one entity depicts, represents, or characterizes another entity as being in a specific kind of relationship with it or with a third party.
-
B.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
C.
portraysCharacterRelationship
Indicates that one entity depicts or represents the relationship between characters in another entity.
-
D.
portraysRelation
Indicates that one entity depicts, represents, or acts in the role of another entity within some medium or context.
-
E.
showsRelationshipWith
Indicates that one entity visually or explicitly presents or demonstrates its connection or association with another entity.
- 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: May 1, 2026, 1:02 a.m.