Triple
T17109280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krasnoye Sormovo Factory |
E415181
|
entity |
| Predicate | hasPlantNumber |
P125970
|
FINISHED |
| Object | 112 |
—
|
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: 112 | Statement: [Krasnoye Sormovo Factory, hasPlantNumber, 112]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlantNumber Context triple: [Krasnoye Sormovo Factory, hasPlantNumber, 112]
-
A.
hasPlantSymbol
Indicates that an entity is associated with or represented by a particular plant as its symbolic emblem or sign.
-
B.
numberOfPlants
Indicates the total count of plants associated with a given entity or context.
-
C.
hasPlantCategory
Indicates that one entity is assigned to, or classified under, a particular plant-related category or type.
-
D.
hasPlantPart
Indicates that one entity includes, contains, or is composed of a specific plant part of another entity.
-
E.
hasMajorPlant
Indicates that one entity possesses or hosts a primary or most significant plant facility or installation in relation to another entity.
- F. None of above. chosen
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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2906a081909d0d43cf04319f52 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.