Triple
T32117363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaffer Conservatory |
E820273
|
entity |
| Predicate | hasNotableStudentFictional |
P198418
|
FINISHED |
| Object | Andrew Neiman |
—
|
NE NERFINISHED |
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: Andrew Neiman | Statement: [Shaffer Conservatory, hasNotableStudentFictional, Andrew Neiman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableStudentFictional Context triple: [Shaffer Conservatory, hasNotableStudentFictional, Andrew Neiman]
-
A.
hasStudentFictional
chosen
Indicates that an entity has, is associated with, or is characterized by a student who is fictional rather than real.
-
B.
hasNotableTeacherFictional
Indicates that a fictional entity has a notable teacher within a narrative or fictional context.
-
C.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
D.
hasNotableWriter
Indicates that an entity is associated with a writer who is recognized as significant or distinguished in some notable way.
-
E.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
- 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_69f3490209c881908ec0241476715f15 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01185c46f0819089b4a2ad3c3e2f33 |
completed | May 10, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_6a0117e19e008190870663dd45084416 |
completed | May 10, 2026, 11:42 p.m. |
Created at: May 1, 2026, 12:28 a.m.