Triple
T3515597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymond Asquith |
E74298
|
entity |
| Predicate | academicAchievement |
P26684
|
FINISHED |
| Object | First-class degree in Literae Humaniores |
—
|
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: First-class degree in Literae Humaniores | Statement: [Raymond Asquith, academicAchievement, First-class degree in Literae Humaniores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicAchievement Context triple: [Raymond Asquith, academicAchievement, First-class degree in Literae Humaniores]
-
A.
collegeAchievement
chosen
Indicates that an entity has attained a specific level of success, recognition, or accomplishment in a college or higher-education context.
-
B.
highSchoolAchievement
Indicates the level or nature of a person’s academic or related performance outcomes during their high school education.
-
C.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
D.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
E.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc30362c81908ca7497a6a935cc6 |
completed | March 8, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69adae10689c8190b7dc6d7daa8295b6 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.