Triple
T25990425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanley T. Banks |
E646332
|
entity |
| Predicate | relationshipToKayBanks |
P194975
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Stanley T. Banks, relationshipToKayBanks, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKayBanks Context triple: [Stanley T. Banks, relationshipToKayBanks, father]
-
A.
relationshipToKenny
Indicates the specific familial, social, or interpersonal connection that one entity has to Kenny.
-
B.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
-
C.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
D.
relationshipToRyanBingham
Indicates the specific type of personal or social relationship an entity has with Ryan Bingham.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- 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_69e77e88cb8481908da31d4a00661f55 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69fd974c0e8481909fdd312897c647b3 |
completed | May 8, 2026, 7:57 a.m. |
Created at: April 22, 2026, 8:57 a.m.