Triple
T24121021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amanda Bonner |
E597651
|
entity |
| Predicate | relationshipTypeWithAdamBonner |
P154929
|
FINISHED |
| Object | married couple |
—
|
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: married couple | Statement: [Amanda Bonner, relationshipTypeWithAdamBonner, married couple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithAdamBonner Context triple: [Amanda Bonner, relationshipTypeWithAdamBonner, married couple]
-
A.
relationshipTypeWithSeanBoswell
Indicates the specific nature or category of relationship that an entity has with Sean Boswell.
-
B.
relationshipTypeWithHudBannon
Indicates the specific nature or category of relationship that an entity has with the person or entity named Hud Bannon.
-
C.
relationshipTypeWithBobbyBoucher
Indicates the specific nature or category of relationship that an entity has with Bobby Boucher.
-
D.
relationshipToAddieBundren
Indicates the specific familial, social, or emotional relationship that one entity has to Addie Bundren.
-
E.
relationshipTypeWithJeffSadecki
Indicates the specific nature or category of relationship that an entity has with Jeff Sadecki.
- 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_69e288c74200819098ab875b592cb39f |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee2defc81909df55900769fef5b |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 11:05 p.m.