Triple
T19473109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivoclar Vivadent |
E487173
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Ramco AG |
—
|
NE NERFINISHED |
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: Ramco AG | Statement: [Ivoclar Vivadent, formerName, Ramco AG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramco AG Context triple: [Ivoclar Vivadent, formerName, Ramco AG]
-
A.
Ramco AG
chosen
Ramco AG was the original corporate entity that later evolved into Ivoclar Vivadent, a major global manufacturer of dental materials and technologies.
-
B.
Ramo-Wooldridge Corporation
Ramo-Wooldridge Corporation was a pioneering American aerospace and defense contractor that played a key role in early U.S. missile and space programs before evolving into part of TRW Inc.
-
C.
Aral AG
Aral AG is a major German brand of fuel stations and petroleum products, widely recognized for its network of service stations across Germany.
-
D.
Ankogel Group
The Ankogel Group is a subrange of the Austrian Alps known for its high peaks, glaciated terrain, and popular mountaineering and skiing areas.
-
E.
Marcus Corporation
Marcus Corporation is a U.S.-based company best known for its movie theatre and hospitality businesses, including operating cinema chains and hotels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e633ea604c8190a2feacb709b7ca27 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:39 p.m.