Triple
T30780599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accepted |
E783797
|
entity |
| Predicate | fictionalInstitution |
P29320
|
FINISHED |
| Object | South Harmon Institute of Technology |
—
|
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: South Harmon Institute of Technology | Statement: [Accepted, fictionalInstitution, South Harmon Institute of Technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalInstitution Context triple: [Accepted, fictionalInstitution, South Harmon Institute of Technology]
-
A.
fictionalUniversityAffiliation
Indicates that an entity is affiliated with a university that exists only in a fictional or imaginary context.
-
B.
hasFictionalSchool
chosen
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
C.
fictionalBuilding
Indicates that a building is imaginary or exists only within a fictional or invented context.
-
D.
fictionalEntityIn
Indicates that a fictional entity appears in, is set within, or is part of the context of another work, setting, or universe.
-
E.
fictionalHospital
Indicates that a hospital is imaginary or exists only within a fictional or narrative context, rather than in reality.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd474b7e788190a9bb9b542d878f60 |
completed | May 8, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69fd46d8b2f0819099d92d72c902f60e |
completed | May 8, 2026, 2:13 a.m. |
Created at: April 29, 2026, 8:41 p.m.