Triple
T6360725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British earldoms |
E143099
|
entity |
| Predicate | femaleCourtesyTitle |
P2097
|
FINISHED |
| Object | Lady |
—
|
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: Lady | Statement: [British earldoms, femaleCourtesyTitle, Lady]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleCourtesyTitle Context triple: [British earldoms, femaleCourtesyTitle, Lady]
-
A.
officeHolderTitleWhenFemale
Indicates the specific title used for a person holding an office when that office holder is female.
-
B.
traditionalCourtesyTitleHeir
Indicates that one entity holds the customary or historically recognized courtesy title associated with being the heir of another entity.
-
C.
motherTitle
Indicates the formal title or honorific associated with a person's mother.
-
D.
aristocraticTitleBeforeMarriage
Indicates that the subject held a specific aristocratic title prior to entering into marriage.
-
E.
honorificTitle
chosen
Indicates that one entity serves as a formal honorific or respectful title used to address or refer to another entity.
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067fa0d0c819098d01545849142fc |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:32 p.m.