Triple
T33703208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flynn-Fletcher family |
E863513
|
entity |
| Predicate | hasMaritalRelationship |
P64467
|
FINISHED |
| Object | Linda Flynn-Fletcher and Lawrence Fletcher |
—
|
NE NERFINISHED |
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: Linda Flynn-Fletcher and Lawrence Fletcher | Statement: [Flynn-Fletcher family, hasMaritalRelationship, Linda Flynn-Fletcher and Lawrence Fletcher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalRelationship Context triple: [Flynn-Fletcher family, hasMaritalRelationship, Linda Flynn-Fletcher and Lawrence Fletcher]
-
A.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
B.
maritalRelations
chosen
Indicates a legally or socially recognized spousal relationship or marriage-based connection between two entities.
-
C.
hasMaritalFunction
Indicates that one entity serves a role or performs a function within the context of a marital relationship or institution.
-
D.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
E.
isMarriedToA
Indicates that one entity is legally and socially bound in marriage to another specific entity.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01295195748190b896d99c3d1f6134 |
completed | May 11, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_6a0128fe96dc8190a73715ab08752dd1 |
completed | May 11, 2026, 12:55 a.m. |
Created at: May 1, 2026, 1:43 a.m.