Triple
T31154076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gotham University |
E794154
|
entity |
| Predicate | typeOfInstitutionInFiction |
P71478
|
FINISHED |
| Object | higher-education institution |
—
|
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: higher-education institution | Statement: [Gotham University, typeOfInstitutionInFiction, higher-education institution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfInstitutionInFiction Context triple: [Gotham University, typeOfInstitutionInFiction, higher-education institution]
-
A.
fictionalEntityType
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
-
B.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
C.
fictionalUniversityAffiliation
Indicates that an entity is affiliated with a university that exists only in a fictional or imaginary context.
-
D.
hasFictionalEstablishmentType
chosen
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
E.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ffb5c373948190a6606e8caa87a384 |
completed | May 9, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ffb261da788190b41399df8ed895e8 |
completed | May 9, 2026, 10:17 p.m. |
Created at: April 29, 2026, 9:06 p.m.