Triple
T350320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Engineering, University of California, Berkeley |
E7426
|
entity |
| Predicate | hasNotableAlumniIn |
P4387
|
FINISHED |
| Object | technology industry |
—
|
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: technology industry | Statement: [College of Engineering, University of California, Berkeley, hasNotableAlumniIn, technology industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAlumniIn Context triple: [College of Engineering, University of California, Berkeley, hasNotableAlumniIn, technology industry]
-
A.
hasNotableAlumniType
chosen
Indicates that an entity has notable alumni belonging to a specified category or type.
-
B.
hasNotableHonoree
Indicates that an entity is notably dedicated to, named after, or honors a particular person or group.
-
C.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
D.
notableStudent
Indicates that a person is a distinguished or particularly significant student of another individual or institution.
-
E.
notableInstitution
Indicates that an institution holds particular significance, prominence, or recognition in relation to the subject.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb1f028c819098fa6480b4ca5cf0 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e955d1f88190bd687c46fa7c5469 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.