Triple
T28521557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malachai |
E721783
|
entity |
| Predicate | fromFictionalLocation |
P84403
|
FINISHED |
| Object | Gatlin, Nebraska |
—
|
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: Gatlin, Nebraska | Statement: [Malachai, fromFictionalLocation, Gatlin, Nebraska]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fromFictionalLocation Context triple: [Malachai, fromFictionalLocation, Gatlin, Nebraska]
-
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.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
C.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
D.
fictionalLocationAssociatedWith
chosen
Indicates a relationship where a fictional entity (such as a character, event, or work) is connected to or set in a particular fictional location.
-
E.
notableFictionalLocationIn
Indicates that a fictional location is notably situated within or strongly associated with a particular larger place or setting.
- 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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64fa24a6481908c8b6651cbaf0664 |
completed | May 2, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:21 a.m.