Triple
T33343635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lutz |
E853736
|
entity |
| Predicate | regionTypeInFiction |
P114636
|
FINISHED |
| Object | urban center in Zubrowka |
—
|
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: urban center in Zubrowka | Statement: [Lutz, regionTypeInFiction, urban center in Zubrowka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionTypeInFiction Context triple: [Lutz, regionTypeInFiction, urban center in Zubrowka]
-
A.
countryTypeInFiction
Indicates that a country is classified according to its role or nature within a fictional context (e.g., fictional, real-but-fictionalized, alternate-history, etc.).
-
B.
fictionalSettingRegion
chosen
Indicates that a fictional setting is located within or associated with a specific geographic or administrative region.
-
C.
associatedWithRegionInFiction
Indicates that, within a fictional context, an entity is linked or connected to a particular region or geographic area.
-
D.
fictionalRegionalIdentity
Indicates that an entity is associated with, or characterized by, an invented or imaginary regional or local identity.
-
E.
regionTypeOfPlace
Indicates that a place belongs to or is categorized under a specific type of geographic or administrative region.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
Created at: May 1, 2026, 1:34 a.m.