Triple
T20451907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir David Lewis |
E501672
|
entity |
| Predicate | hasAlmaMater |
P86301
|
FINISHED |
| Object | Jesus College, Oxford |
—
|
NE NERFINISHED |
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: Jesus College, Oxford | Statement: [Sir David Lewis, hasAlmaMater, Jesus College, Oxford]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlmaMater Context triple: [Sir David Lewis, hasAlmaMater, Jesus College, Oxford]
-
A.
servesAsAlmaMaterOf
chosen
Indicates that an educational institution is the alma mater of a person or entity, meaning they previously studied or graduated there.
-
B.
notableAlmaMater
Indicates that an educational institution is a particularly significant or distinguished alma mater of a person or entity, beyond merely having attended or graduated.
-
C.
isStudiedIn
Indicates that a subject (such as a topic, field, or phenomenon) is examined, researched, or learned about within a particular context, environment, or discipline.
-
D.
hasUniversities
Indicates that an entity possesses, contains, or is associated with one or more universities.
-
E.
hasFormerInstitution
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68d0296ac819081e74c67d3cc6349 |
completed | April 20, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:32 a.m.