Triple
T4953463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voith |
E111223
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Voith Paper |
E111223
|
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: Voith Paper | Statement: [Voith, hasSubsidiary, Voith Paper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Voith Paper Context triple: [Voith, hasSubsidiary, Voith Paper]
-
A.
Voith
chosen
Voith is a German multinational engineering company known for its technologies and services in sectors such as energy, paper, raw materials, and transportation.
-
B.
UPM
UPM is the Polytechnic University of Madrid, a leading Spanish public university specializing in engineering, architecture, and technology.
-
C.
Bühler
Bühler is a German-language surname borne by various notable individuals across fields such as politics, sports, and academia.
-
D.
International Paper
International Paper is a leading global producer of renewable fiber-based packaging, pulp, and paper products.
-
E.
Georgia-Pacific
Georgia-Pacific is a major American pulp and paper company known for producing tissue, packaging, building products, and related chemicals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71b82dd88190adfb08c3b3191fe0 |
completed | March 20, 2026, 4:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81d773bc8190861be7ad83de6c2a |
completed | March 21, 2026, 11:32 a.m. |
Created at: March 20, 2026, 1:31 p.m.