Triple
T2192371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Education in a Divided World |
E49890
|
entity |
| Predicate | authorNotablePosition |
P938
|
FINISHED |
| Object | President of Harvard 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: President of Harvard University | Statement: [Education in a Divided World, authorNotablePosition, President of Harvard University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorNotablePosition Context triple: [Education in a Divided World, authorNotablePosition, President of Harvard University]
-
A.
notableWorkRole
Indicates that a person’s role or position is specifically associated with the creation, performance, or contribution to a notable work.
-
B.
holderNotableFor
Indicates that a holder (such as a person or organization) is particularly known or recognized for a specific role, achievement, work, or characteristic.
-
C.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
D.
notableHolderRole
Indicates that an entity is recognized for holding a particular role, office, or position in a notable or distinguished capacity.
-
E.
authorOccupation
chosen
Indicates the professional role or job that an author holds or is associated with.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf48ceb48190956df39377df0548 |
completed | March 7, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.