Triple
T6672193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Дьокуускай |
E151756
|
entity |
| Predicate | populationRankInFarEast |
P25930
|
FINISHED |
| Object | one of the largest cities in the Russian Far East |
—
|
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: one of the largest cities in the Russian Far East | Statement: [Дьокуускай, populationRankInFarEast, one of the largest cities in the Russian Far East]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInFarEast Context triple: [Дьокуускай, populationRankInFarEast, one of the largest cities in the Russian Far East]
-
A.
hasPopulationRankInRegion
chosen
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
-
B.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
rankByLengthInAsia
Indicates that entities are ordered or compared based on their length within the context of Asia.
-
D.
populationRankInIndonesia
Indicates the relative position of an entity in terms of population size compared to other entities within Indonesia.
-
E.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.