Triple
T16682641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Almer |
E405376
|
entity |
| Predicate | hasNotableStudentOrClient |
P48
|
FINISHED |
| Object | British alpinists |
—
|
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: British alpinists | Statement: [Christian Almer, hasNotableStudentOrClient, British alpinists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableStudentOrClient Context triple: [Christian Almer, hasNotableStudentOrClient, British alpinists]
-
A.
hasNotableClientWork
Indicates that an entity has performed significant or noteworthy work or services for a particular client.
-
B.
hasStudents
chosen
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
C.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
D.
hasNotableClientType
Indicates that an entity has clients belonging to a particular notable or distinguished category or type.
-
E.
hasNotableInstitutionType
Indicates that an entity is associated with, or characterized by, a particular type or category of notable institution.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d7018448190b3cb23191322044e |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.