Triple
T5401329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KUKA |
E120783
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | KUKA Systems |
E120783
|
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: KUKA Systems | Statement: [KUKA, subsidiary, KUKA Systems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KUKA Systems Context triple: [KUKA, subsidiary, KUKA Systems]
-
A.
KUKA
chosen
KUKA is a German industrial robotics and automation company known for its advanced robotic arms used in manufacturing and entertainment applications.
-
B.
Rethink Robotics
Rethink Robotics was a robotics company known for developing collaborative industrial robots like Baxter and Sawyer designed to work safely alongside humans in manufacturing environments.
-
C.
ABB Robotics
ABB Robotics is a leading global provider of industrial robots and automation solutions used across manufacturing, logistics, and other industries.
-
D.
Siemens
Siemens is a major German multinational conglomerate best known for its leading roles in industrial manufacturing, energy, healthcare technology, and infrastructure solutions worldwide.
-
E.
Boston Dynamics
Boston Dynamics is an American engineering and robotics company renowned for creating advanced, highly mobile robots such as Atlas, Spot, and Handle.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8771b25c819080da247bc3164cd9 |
completed | March 20, 2026, 5:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3a9e104881908d6012c87f30061b |
completed | March 22, 2026, 12:41 a.m. |
Created at: March 20, 2026, 2:04 p.m.