Triple
T34804615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daddy Johnson |
E1003318
|
entity |
| Predicate | relationshipToNavin R. Johnson |
P205561
|
FINISHED |
| Object | loving adoptive 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: loving adoptive father | Statement: [Daddy Johnson, relationshipToNavin R. Johnson, loving adoptive father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToNavin R. Johnson Context triple: [Daddy Johnson, relationshipToNavin R. Johnson, loving adoptive father]
-
A.
relationshipTypeWith Francesca Johnson
Indicates the specific nature or category of the relationship that an entity has with Francesca Johnson.
-
B.
relationshipToNina
Indicates that one entity has a specified personal or social relationship to Nina.
-
C.
relationshipWithJohn "Joker" Jackson
Indicates that the subject has a specified type of relationship with the person known as John "Joker" Jackson.
-
D.
relationshipTypeWithJoshSrebnick
Indicates the specific nature or category of the relationship that an entity has with Josh Srebnick.
-
E.
relationshipToNicole
Indicates the specific type of relationship or connection that an entity has with Nicole.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 3:59 p.m.