Triple
T7612602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourbon (by marriage) |
E172278
|
entity |
| Predicate | typicalGenderDistribution |
P34349
|
FINISHED |
| Object | predominantly female due to historical patterns of dynastic marriage |
—
|
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: predominantly female due to historical patterns of dynastic marriage | Statement: [Bourbon (by marriage), typicalGenderDistribution, predominantly female due to historical patterns of dynastic marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGenderDistribution Context triple: [Bourbon (by marriage), typicalGenderDistribution, predominantly female due to historical patterns of dynastic marriage]
-
A.
genderOfResidents
Indicates the gender identity or classification associated with the residents of a particular place or group.
-
B.
hasTypicalGenderAssociation
chosen
Indicates that one entity is commonly or culturally associated with a particular gender more than with other genders.
-
C.
hasGenderDistributionIssues
Indicates that the entity exhibits problems, imbalances, or inequities related to the distribution or representation of different genders.
-
D.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
E.
genderOfTypicalHolder
Indicates the gender that is most commonly associated with or typical of the usual holder of something.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa23981c81908168ac0ac9add5d8 |
completed | March 27, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e485f88190910b39da52a955fe |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:55 p.m.