Triple
T31373594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Art Donaldson |
E800231
|
entity |
| Predicate | relationshipTypeWith Tashi Duncan |
P207414
|
FINISHED |
| Object | coach–player history and marriage |
—
|
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: coach–player history and marriage | Statement: [Art Donaldson, relationshipTypeWith Tashi Duncan, coach–player history and marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Tashi Duncan Context triple: [Art Donaldson, relationshipTypeWith Tashi Duncan, coach–player history and marriage]
-
A.
relationshipTypeWith Dolly Talbo
Indicates the specific nature or category of the relationship that an entity has with Dolly Talbo.
-
B.
hasRelationshipTypeWith Tai Frasier
Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
-
C.
relationshipTypeWithTaylorTravis
Indicates the specific nature or category of the relationship that an entity has with Taylor Travis.
-
D.
relationshipToTina
Indicates the specific type of personal or social relationship that an entity has with Tina.
-
E.
relationshipToTucker
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
- 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_69f224e84da08190abfc2f17494a33c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 9:18 p.m.