Triple
T5072492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Potter and the Forbidden Journey |
E114312
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | KUKA |
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 | Statement: [Harry Potter and the Forbidden Journey, manufacturer, KUKA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KUKA Context triple: [Harry Potter and the Forbidden Journey, manufacturer, KUKA]
-
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.
ABB Robotics
ABB Robotics is a leading global provider of industrial robots and automation solutions used across manufacturing, logistics, and other industries.
-
C.
Kinetix
Kinetix is Rockwell Automation’s line of motion control products and servo drives used for precise, integrated industrial automation.
-
D.
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.
-
E.
Kawada Industries
Kawada Industries is a Japanese engineering and construction company known for its work on major infrastructure projects, including prominent bridges and civil works.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74ce140881909a2874663244c0db |
completed | March 20, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb11600ac81908661759839ebfc98 |
completed | March 21, 2026, 2:54 p.m. |
Created at: March 20, 2026, 1:39 p.m.