Triple
T34962681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Могилёв-Подольский |
E1008301
|
entity |
| Predicate | имеетПромышленность |
P20603
|
FINISHED |
| Object | пищевая промышленность |
—
|
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: пищевая промышленность | Statement: [Могилёв-Подольский, имеетПромышленность, пищевая промышленность]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: имеетПромышленность Context triple: [Могилёв-Подольский, имеетПромышленность, пищевая промышленность]
-
A.
industrialStructure
Indicates a structural or organizational relationship involving industrial facilities, systems, or frameworks.
-
B.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
C.
industrialCategory
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
-
D.
industrialFocus
Indicates a relationship where an entity is primarily concerned with, specialized in, or directed toward a particular industrial sector or area of industrial activity.
-
E.
hasIndustrialCompany
Indicates that one entity possesses, controls, or is associated with an industrial company.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4 p.m.