Triple
T35020605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerry Kennedy |
E1010183
|
entity |
| Predicate | relationshipTypeWithHollyKennedy |
P206810
|
FINISHED |
| Object | loving husband |
—
|
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 husband | Statement: [Gerry Kennedy, relationshipTypeWithHollyKennedy, loving husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithHollyKennedy Context triple: [Gerry Kennedy, relationshipTypeWithHollyKennedy, loving husband]
-
A.
relationshipToJodieHolmes
Indicates the nature or type of relationship an entity has with Jodie Holmes.
-
B.
relationshipTypeWithMelanieHealy
Indicates the specific nature or category of relationship that an entity has with Melanie Healy.
-
C.
relationshipWithKateMoseley
Indicates that one entity has a specified type of relationship or connection with Kate Moseley.
-
D.
relationshipToHollyGolightly
Indicates the nature or type of relationship an entity has with Holly Golightly.
-
E.
relationshipTypeWithGingerMcKenna
Indicates the specific nature or category of relationship an entity has with Ginger McKenna.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
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, 4:01 p.m.