Triple
T7071083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith Black |
E164696
|
entity |
| Predicate | spouseRelationshipContext |
P74827
|
FINISHED |
| Object | marital difficulties |
—
|
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: marital difficulties | Statement: [Meredith Black, spouseRelationshipContext, marital difficulties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseRelationshipContext Context triple: [Meredith Black, spouseRelationshipContext, marital difficulties]
-
A.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
D.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
E.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
- F. None of above. chosen
Provenance (4 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c862f481908d1faf6ed57774f1 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:39 p.m.