Triple
T35285972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow–St. Petersburg corridor |
E1019083
|
entity |
| Predicate | supportsUrbanAreas |
P70324
|
FINISHED |
| Object | Moscow metropolitan area |
E804701
|
NE 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: Moscow metropolitan area | Statement: [Moscow–St. Petersburg corridor, supportsUrbanAreas, Moscow metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsUrbanAreas Context triple: [Moscow–St. Petersburg corridor, supportsUrbanAreas, Moscow metropolitan area]
-
A.
coversUrbanAreas
chosen
Indicates that something extends over, includes, or provides coverage for urban or metropolitan areas.
-
B.
statusInUrbanAreas
Indicates the condition, prevalence, or situation of something specifically within urban areas.
-
C.
significantUrbanArea
Indicates that a location is classified as a major or important urban center within a broader geographic or administrative context.
-
D.
hasMostOfUrbanAreasOf
Indicates that one entity contains or encompasses the majority of the urban areas belonging to another entity.
-
E.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
- F. None of above.
Provenance (4 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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3823b9225081908968e6650b362cf7 |
completed | June 21, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.