Triple
T10226437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yosser Hughes |
E243214
|
entity |
| Predicate | fictionalMaritalStatus |
P92865
|
FINISHED |
| Object | separated |
—
|
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: separated | Statement: [Yosser Hughes, fictionalMaritalStatus, separated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalMaritalStatus Context triple: [Yosser Hughes, fictionalMaritalStatus, separated]
-
A.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
B.
fictionalBirthStatus
Indicates the relationship between an entity and its status of being born or created within a fictional or imaginary context.
-
C.
fictionalStatus
Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
-
D.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
E.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d23a9c4c8190abece9e52879c479 |
completed | April 7, 2026, 9:45 a.m. |
Created at: April 6, 2026, 11:17 a.m.