Triple
T25545317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Rogo |
E640282
|
entity |
| Predicate | hasRelationshipTypeWithSpouse |
P56596
|
FINISHED |
| Object | protective |
—
|
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: protective | Statement: [Linda Rogo, hasRelationshipTypeWithSpouse, protective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithSpouse Context triple: [Linda Rogo, hasRelationshipTypeWithSpouse, protective]
-
A.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
B.
hasMaritalRelationshipType
chosen
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
C.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
D.
relationshipToSpouse
Indicates the specific familial or social role one person holds in relation to their spouse (e.g., husband, wife, partner).
-
E.
spouseOfInstanceOf
Indicates that one entity is the spouse of another entity that is an instance of a specified class or type.
- 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_69e75dbfff7081909b0aa779d48321d2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: April 21, 2026, 3:28 p.m.