Triple
T33688338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald Ratner |
E863100
|
entity |
| Predicate | hasNotableAlmaMater |
P47801
|
FINISHED |
| Object | University of Chicago |
E8795
|
NE 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: University of Chicago | Statement: [Gerald Ratner, hasNotableAlmaMater, University of Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAlmaMater Context triple: [Gerald Ratner, hasNotableAlmaMater, University of Chicago]
-
A.
usesAlmaMater
Indicates that one entity makes use of, relies on, or leverages the educational institution where another entity studied or graduated.
-
B.
notableAlmaMater
chosen
Indicates that an educational institution is a particularly significant or distinguished alma mater of a person or entity, beyond merely having attended or graduated.
-
C.
performsAlmaMater
Indicates that an entity (typically a performer or group) gives a performance of another entity’s alma mater song or anthem.
-
D.
hasNotableBusinessSchool
Indicates that an institution possesses a business school recognized for its prominence, reputation, or significant impact.
-
E.
hasNotableAlumniInstitution
Indicates that an institution is associated with one or more notable alumni who previously attended or graduated from it.
- F. None of above.
Provenance (4 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_69f3498662b48190904442c39df84fb7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01d9ca07b88190b4ad70b6336447b6 |
completed | May 11, 2026, 1:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3692c0c8c08190acb8e7e3a10e3d65 |
completed | June 20, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_6a01d807c3048190b79f0b6b933dd3b7 |
completed | May 11, 2026, 1:22 p.m. |
Created at: May 1, 2026, 1:43 a.m.