Triple
T1728901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl Butz |
E37563
|
entity |
| Predicate | academicTitle |
P9647
|
FINISHED |
| Object | dean of agriculture at Purdue University |
—
|
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: dean of agriculture at Purdue University | Statement: [Earl Butz, academicTitle, dean of agriculture at Purdue University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicTitle Context triple: [Earl Butz, academicTitle, dean of agriculture at Purdue University]
-
A.
academicTitleAbbreviation
Indicates that one entity is the standard abbreviated form of another entity’s full academic title.
-
B.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
C.
creditedTitle
chosen
Indicates that a particular title or role is formally attributed to an entity as a credit.
-
D.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
E.
honorificTitle
Indicates that one entity serves as a formal honorific or respectful title used to address or refer to another entity.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.