Triple
T19486098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rēzekne, Latvian SSR, Soviet Union |
E487514
|
entity |
| Predicate | hadIndustrialSector |
P20603
|
FINISHED |
| Object | light industry |
—
|
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: light industry | Statement: [Rēzekne, Latvian SSR, Soviet Union, hadIndustrialSector, light industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadIndustrialSector Context triple: [Rēzekne, Latvian SSR, Soviet Union, hadIndustrialSector, light industry]
-
A.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
B.
hasIndustrialDevelopment
Indicates that an entity possesses, supports, or is characterized by industrial growth, infrastructure, or manufacturing-related development.
-
C.
industrialStructure
Indicates a structural or organizational relationship involving industrial facilities, systems, or frameworks.
-
D.
industrialCategory
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
-
E.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343f46e88190b7ba65c210285bee |
completed | April 20, 2026, 2:12 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7883308190b73912a71a35a835 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:39 p.m.