Triple
T22608612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanford W. Ascherman Professor of Computer Science |
E566631
|
entity |
| Predicate | holderFieldOfExpertise |
P140458
|
FINISHED |
| Object | database theory |
—
|
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: database theory | Statement: [Stanford W. Ascherman Professor of Computer Science, holderFieldOfExpertise, database theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holderFieldOfExpertise Context triple: [Stanford W. Ascherman Professor of Computer Science, holderFieldOfExpertise, database theory]
-
A.
subjectSpecialization
chosen
Indicates that one subject focuses on, or has expertise in, a particular field, topic, or area of knowledge.
-
B.
characterFieldOfStudy
Indicates the academic or disciplinary field that a character studies or specializes in.
-
C.
basedOnExpertiseOf
Indicates that something is determined, derived, or justified using the knowledge, skills, or judgment of a particular expert or group of experts.
-
D.
skilledIn
Indicates that an entity possesses ability, expertise, or proficiency in performing or using another entity (such as a task, tool, or domain).
-
E.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
- 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_69e245884860819081046ce07d5872c4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f167e86794819097e9c1ea83db52e6 |
completed | April 29, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:55 p.m.