Triple
T5117521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eva Peace |
E115373
|
entity |
| Predicate | fictionalLocationType |
P16688
|
FINISHED |
| Object | African American community in Medallion, Ohio |
—
|
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: African American community in Medallion, Ohio | Statement: [Eva Peace, fictionalLocationType, African American community in Medallion, Ohio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalLocationType Context triple: [Eva Peace, fictionalLocationType, African American community in Medallion, Ohio]
-
A.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
B.
fictionalUniverseLocation
Indicates that one entity is a location or setting within the fictional universe to which the other entity belongs or in which it takes place.
-
C.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
D.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
E.
cityOfFictionalActivity
Indicates that a fictional activity, event, or storyline takes place in the specified city.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7d5a23908190a24e79d1b29d6fcf |
completed | March 20, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69bd77aa68b88190a50dd736a72d2901 |
completed | March 20, 2026, 4:36 p.m. |
Created at: March 20, 2026, 1:41 p.m.