Triple
T35509987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Dorie |
E1026260
|
entity |
| Predicate | relationshipTypeWithJuneDorie |
P207013
|
FINISHED |
| Object | tragic love story |
—
|
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: tragic love story | Statement: [John Dorie, relationshipTypeWithJuneDorie, tragic love story]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithJuneDorie Context triple: [John Dorie, relationshipTypeWithJuneDorie, tragic love story]
-
A.
relationshipTypeWithNedDorsey
Indicates the specific nature or category of relationship that an entity has with Ned Dorsey.
-
B.
relationshipTypeWithDoris
Indicates the specific nature or category of the relationship that an entity has with Doris.
-
C.
relationshipToDeloris
Indicates the specific type of personal, familial, or social relationship that one entity has with the entity named Deloris.
-
D.
relationshipToAddieBundren
Indicates the specific familial, social, or emotional relationship that one entity has to Addie Bundren.
-
E.
relationshipTypeWith Dolly Talbo
Indicates the specific nature or category of the relationship that an entity has with Dolly Talbo.
- 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_69f76dfd61208190b93ec6dc439cab41 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.