Triple
T27287436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Collette |
E688516
|
entity |
| Predicate | hasMaritalProblems |
P50123
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Angela Collette, hasMaritalProblems, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalProblems Context triple: [Angela Collette, hasMaritalProblems, true]
-
A.
maritalIssue
chosen
Indicates a relationship where there is conflict, dissatisfaction, or significant strain within a marital or committed partnership.
-
B.
hasMaritalFunction
Indicates that one entity serves a role or performs a function within the context of a marital relationship or institution.
-
C.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
D.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
E.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
- 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_69ef355998e08190bdff849e8f33adce |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
Created at: April 27, 2026, 11:12 a.m.