Triple
T28667068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miskatonic University |
E725611
|
entity |
| Predicate | locatedInRegionFictional |
P136812
|
FINISHED |
| Object | New England |
—
|
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: New England | Statement: [Miskatonic University, locatedInRegionFictional, New England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInRegionFictional Context triple: [Miskatonic University, locatedInRegionFictional, New England]
-
A.
belongsToFictionalRegion
chosen
Indicates that an entity is located within, associated with, or under the jurisdiction of a fictional or imaginary geographic region.
-
B.
locatedInFictionalCountry
Indicates that an entity exists or is situated within a country that is fictional rather than real.
-
C.
fictionalSettingRegion
Indicates that a fictional setting is located within or associated with a specific geographic or administrative region.
-
D.
locatedInFictionalContext
Indicates that one entity exists or occurs within the setting or universe of a fictional work associated with another entity.
-
E.
residesInFictionalLocation
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
- 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69ff8ba3f8248190bbdf8e7ec2b35093 |
completed | May 9, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69ff8b41ba988190a7332e8317d10f09 |
completed | May 9, 2026, 7:30 p.m. |
Created at: April 28, 2026, 5:01 a.m.