Triple
T21875830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregory Larkin |
E540142
|
entity |
| Predicate | relationshipTypeWithRoseMorgan |
P142888
|
FINISHED |
| Object | 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: marriage | Statement: [Gregory Larkin, relationshipTypeWithRoseMorgan, marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithRoseMorgan Context triple: [Gregory Larkin, relationshipTypeWithRoseMorgan, marriage]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipTestedBy
Indicates that a relationship between entities has been examined or evaluated by a specified agent, method, or test.
-
C.
relationshipToBond
Indicates the specific type of personal, familial, or professional relationship an entity has to the person named Bond.
-
D.
relationshipTypeWithSassi
chosen
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
E.
lifePartnerType
Indicates the type or category of a person’s life partner in a long-term or committed relationship.
- F. None of above.
Provenance (3 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f33957f481908789b054a4fd1b77 |
completed | April 28, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:02 p.m.