Triple
T27785507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs Cheveley |
E700947
|
entity |
| Predicate | hasMaritalStatusInFiction |
P92865
|
FINISHED |
| Object | married woman ("Mrs.") |
—
|
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: married woman ("Mrs.") | Statement: [Mrs Cheveley, hasMaritalStatusInFiction, married woman ("Mrs.")]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalStatusInFiction
Context triple: [Mrs Cheveley, hasMaritalStatusInFiction, married woman ("Mrs.")]
-
A.
fictionalMaritalStatus
chosen
Indicates that an entity has a marital status that exists only within a fictional, narrative, or hypothetical context rather than in real life.
-
B.
maritalStatusInMyth
Indicates the marital status or relationship state of an entity as portrayed within a specific myth or mythological tradition.
-
C.
maritalStatusInDisguise
Indicates that an entity’s true marital status is being concealed or misrepresented, typically appearing different from what it actually is.
-
D.
maritalStatusInLegend
Indicates the marital status attributed to an entity within a legend, myth, or traditional narrative context.
-
E.
hasAuthorMarriedName
Indicates that an author’s married surname or full married name is associated with them, typically differing from their birth or maiden name.
- 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_69ef6a50d8088190acbf3dfbb06d8091 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: April 27, 2026, 5:24 p.m.