Triple
T36450284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crimean toponymy |
E897989
|
entity |
| Predicate | includesChoronyms |
P73979
|
FINISHED |
| Object | names of regions and districts in Crimea |
—
|
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: names of regions and districts in Crimea | Statement: [Crimean toponymy, includesChoronyms, names of regions and districts in Crimea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesChoronyms Context triple: [Crimean toponymy, includesChoronyms, names of regions and districts in Crimea]
-
A.
toponymContains
Indicates that one geographic place name spatially includes or encompasses another place name within its boundaries.
-
B.
includesToponym
Indicates that one entity contains or references a place name (toponym) associated with another entity.
-
C.
toponymyContainsElement
Indicates that a toponym (place name) includes a specific linguistic or semantic element as part of its composition.
-
D.
hasPlaceNamesIn
chosen
Indicates that something contains, references, or is associated with one or more place names within it.
-
E.
containsSuburbs
Indicates that a larger geographic area or administrative region includes one or more suburbs within its boundaries.
- 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_69f76e5720b481908f8177ac24a7560b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:10 p.m.