Triple
T6236298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonkheer |
E139485
|
entity |
| Predicate | femaleAbbreviation |
P69687
|
FINISHED |
| Object | Jkvr. |
—
|
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: Jkvr. | Statement: [Jonkheer, femaleAbbreviation, Jkvr.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleAbbreviation Context triple: [Jonkheer, femaleAbbreviation, Jkvr.]
-
A.
femaleCommonName
Indicates that the associated name is commonly used as a given name for females.
-
B.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
C.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
-
D.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
-
E.
genderOfEponym
Indicates the gender of the person after whom something (such as a place, object, or concept) is named.
- F. None of above. chosen
Provenance (4 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063021258819093a9237041816638 |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c05707d5408190a1d0fd80414ad957 |
completed | March 22, 2026, 8:54 p.m. |
Created at: March 22, 2026, 4:23 p.m.