Triple
T33873693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Blake |
E868292
|
entity |
| Predicate | hasMaritalHistory |
P94899
|
FINISHED |
| Object | multiple failed marriages |
—
|
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: multiple failed marriages | Statement: [Bad Blake, hasMaritalHistory, multiple failed marriages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalHistory Context triple: [Bad Blake, hasMaritalHistory, multiple failed marriages]
-
A.
characterMaritalHistory
chosen
Indicates a relationship that records the sequence of a character’s past and present marital relationships, including spouses and relevant time periods.
-
B.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
C.
hasMaritalStatusAtEnd
Indicates that an entity possesses a specific marital status at the end of a given period, event, or reference time.
-
D.
hasCivilStatus
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
E.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists 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_69f34995029081909ede0f7df73d1a5e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01487b73488190954eb5143e6f246e |
completed | May 11, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_6a0145210ae481908da59b02efdbc397 |
completed | May 11, 2026, 2:55 a.m. |
Created at: May 1, 2026, 1:47 a.m.