Triple
T36055908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seigneurs of Guernsey fiefs |
E1042946
|
entity |
| Predicate | femaleTitleForm |
P19475
|
FINISHED |
| Object | Dame |
—
|
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: Dame | Statement: [Seigneurs of Guernsey fiefs, femaleTitleForm, Dame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleTitleForm Context triple: [Seigneurs of Guernsey fiefs, femaleTitleForm, Dame]
-
A.
officeHolderTitleWhenFemale
chosen
Indicates the specific title used for a person holding an office when that office holder is female.
-
B.
femaleAbbreviation
Indicates that one entity is an abbreviation or shortened form specifically denoting a female version of another entity.
-
C.
femaleSubject
Indicates that the subject in the relationship or action is female.
-
D.
femaleCounterpartOf
Indicates that one entity is the female equivalent or corresponding counterpart of another entity within a given role, relationship, or category.
-
E.
femaleMember
Indicates that one entity is a member of a group or organization and is identified as female.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.