Triple
T7071088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith Black |
E164696
|
entity |
| Predicate | causeOfFamilyCrisis |
P694
|
FINISHED |
| Object | Walter Black's severe depression |
—
|
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: Walter Black's severe depression | Statement: [Meredith Black, causeOfFamilyCrisis, Walter Black's severe depression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfFamilyCrisis Context triple: [Meredith Black, causeOfFamilyCrisis, Walter Black's severe depression]
-
A.
crisisRelatedTo
Indicates a relationship where one situation, event, or condition is connected to, associated with, or relevant to a crisis.
-
B.
relationshipConflictWith
Indicates a state of opposition, disagreement, or incompatibility between two entities within a relationship.
-
C.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
D.
causeOfDownfall
Indicates a factor, event, or agent that brings about the failure, ruin, or collapse of someone or something.
-
E.
maritalIssue
Indicates a relationship where there is conflict, dissatisfaction, or significant strain within a marital or committed partnership.
- 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_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. |
Created at: March 27, 2026, 2:39 p.m.