Triple
T36450281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crimean toponymy |
E897989
|
entity |
| Predicate | includesHydronyms |
P106673
|
FINISHED |
| Object | names of rivers 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 rivers in Crimea | Statement: [Crimean toponymy, includesHydronyms, names of rivers in Crimea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesHydronyms Context triple: [Crimean toponymy, includesHydronyms, names of rivers in Crimea]
-
A.
hasHydronymOrigin
Indicates that something derives its name from a body of water or hydrological feature.
-
B.
hydronymOf
Indicates that one term is the name of a body of water associated with another geographic entity (e.g., a river, lake, or sea named after a place or feature).
-
C.
hasWatersOf
chosen
Indicates that a geographic or physical entity contains, is traversed by, or is otherwise characterized by specific bodies or types of water.
-
D.
includesToponym
Indicates that one entity contains or references a place name (toponym) associated with another entity.
-
E.
showsHydrography
Indicates that something visually represents or displays bodies of water and related hydrological features.
- 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.