Triple
T38429342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fraser of Strichen |
E903754
|
entity |
| Predicate | hasSurnameDistribution |
P202480
|
FINISHED |
| Object | primarily in northeast Scotland |
—
|
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: primarily in northeast Scotland | Statement: [Fraser of Strichen, hasSurnameDistribution, primarily in northeast Scotland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurnameDistribution Context triple: [Fraser of Strichen, hasSurnameDistribution, primarily in northeast Scotland]
-
A.
hasSurnameFrequency
Indicates that a surname occurs with a specified frequency or rate within a given population or dataset.
-
B.
hasSurnameRank
Indicates that an entity’s surname holds a particular position or rank within an ordered set, such as a list or hierarchy of surnames.
-
C.
hasApproximateNumberOfSurnames
Indicates that an entity is associated with an estimated or approximate count of surnames rather than an exact number.
-
D.
hasSurnameFrequencyReason
Indicates the reason or explanation for the frequency with which a particular surname occurs.
-
E.
possibleSurnameUsage
Indicates that an entity can potentially be used or recognized as a surname for another entity.
- 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_69f76e6a2024819081aa04f4932f89d2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a00868083b081909afc3d8d4ad56b43 |
completed | May 10, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_6a0084f5f72c8190b08afa82690e322a |
completed | May 10, 2026, 1:15 p.m. |
| PDg | Predicate description generation | batch_6a00867f57a48190a4205a859a268998 |
completed | May 10, 2026, 1:22 p.m. |
Created at: May 3, 2026, 4:31 p.m.