Triple
T14761812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinah Barkley |
E346880
|
entity |
| Predicate | relationshipTypeWithJoshBarkley |
P115696
|
FINISHED |
| Object | husband-and-wife performing duo |
—
|
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: husband-and-wife performing duo | Statement: [Dinah Barkley, relationshipTypeWithJoshBarkley, husband-and-wife performing duo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithJoshBarkley Context triple: [Dinah Barkley, relationshipTypeWithJoshBarkley, husband-and-wife performing duo]
-
A.
relationshipTypeWithJoshSrebnick
Indicates the specific nature or category of the relationship that an entity has with Josh Srebnick.
-
B.
relationshipTypeWithJakeBarnes
Indicates the specific nature or category of relationship that an entity has with Jake Barnes.
-
C.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
-
D.
relationshipTypeWithSamMalone
Indicates the specific nature or category of relationship that an entity has with Sam Malone.
-
E.
relationshipToBillyBackus
Indicates the specific familial or social relationship that an entity has to the person named Billy Backus.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f207dc819088a53f717736a121 |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.