Triple
T144536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Illinois at Urbana–Champaign |
E2924
|
entity |
| Predicate | notableAlumniField |
P4387
|
FINISHED |
| Object | engineering |
—
|
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: engineering | Statement: [University of Illinois at Urbana–Champaign, notableAlumniField, engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableAlumniField Context triple: [University of Illinois at Urbana–Champaign, notableAlumniField, engineering]
-
A.
hasNotableAlumniType
chosen
Indicates that an entity has notable alumni belonging to a specified category or type.
-
B.
notableStudent
Indicates that a person is a distinguished or particularly significant student of another individual or institution.
-
C.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
D.
notableStar
Indicates that the subject is a star (or stellar object) that is distinguished or noteworthy in some significant way, such as brightness, fame, or scientific interest, relative to other stars.
-
E.
notableCulturalFigure
Indicates that a person holds significant influence or recognition within a culture’s arts, traditions, values, or public life.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257e935bc8190a03e54a10e9ba6f7 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.