Triple
T8879324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl of Albemarle |
E211367
|
entity |
| Predicate | genderOfTitleHolders |
P78769
|
FINISHED |
| Object | male-preference primogeniture |
—
|
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: male-preference primogeniture | Statement: [Earl of Albemarle, genderOfTitleHolders, male-preference primogeniture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfTitleHolders Context triple: [Earl of Albemarle, genderOfTitleHolders, male-preference primogeniture]
-
A.
hasGenderedTitle
Indicates that an entity is associated with a title or form of address that is explicitly marked for a particular gender.
-
B.
genderOfFirstHolder
Indicates that the relationship specifies the gender of the first entity that holds or possesses something in the described context.
-
C.
genderOfTypicalHolder
Indicates the gender that is most commonly associated with or typical of the usual holder of something.
-
D.
honorificGender
chosen
Indicates that a particular honorific or title is associated with a specific gender or gendered form.
-
E.
genderOfEponym
Indicates the gender of the person after whom something (such as a place, object, or concept) is named.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc614ad1908190a77808fcf7f3e531 |
completed | April 1, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2956788190a311c647b4da17a6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:52 p.m.