Triple
T28294117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brown-Tubbs family |
E713510
|
entity |
| Predicate | hasSpousalRelationshipWithin |
P89337
|
FINISHED |
| Object | Cleveland Brown and Donna Tubbs-Brown |
—
|
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: Cleveland Brown and Donna Tubbs-Brown | Statement: [Brown-Tubbs family, hasSpousalRelationshipWithin, Cleveland Brown and Donna Tubbs-Brown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpousalRelationshipWithin Context triple: [Brown-Tubbs family, hasSpousalRelationshipWithin, Cleveland Brown and Donna Tubbs-Brown]
-
A.
relationshipToSpouse
Indicates the specific familial or social role one person holds in relation to their spouse (e.g., husband, wife, partner).
-
B.
hasSpousePositionInFamily
Indicates that a person’s spouse holds a specific role or position within the family structure.
-
C.
hasMemberSpouseConnection
chosen
Indicates a relationship where one entity is a spouse of a member associated with the other entity.
-
D.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
E.
maritalRelations
Indicates a legally or socially recognized spousal relationship or marriage-based connection between two entities.
- 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_69efb52371d88190a1381c4e58a3b731 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 27, 2026, 11:31 p.m.