Triple
T1653551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Esaki |
E35746
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Sony |
E6422
|
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: Sony | Statement: [Leo Esaki, employer, Sony]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sony Context triple: [Leo Esaki, employer, Sony]
-
A.
Sony
chosen
Sony is a Japanese multinational conglomerate best known for its consumer electronics, gaming (PlayStation), entertainment, and imaging products.
-
B.
Nintendo
Nintendo is a Japanese video game company best known for creating iconic franchises such as Mario, The Legend of Zelda, and Pokémon, as well as popular gaming consoles like the Nintendo Switch.
-
C.
Toyopa Group, LLC
Toyopa Group, LLC is the original corporate name under which the company now known as Snap Inc., the parent of Snapchat, was first established.
-
D.
PlayStation
PlayStation is a popular line of video game consoles and gaming platforms developed by Sony, known for its extensive library of exclusive titles and global influence on the gaming industry.
-
E.
Toshiba
Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a8a080c8190b6913d6830d74526 |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad60ac133881909222b25029096407 |
completed | March 8, 2026, 11:42 a.m. |
Created at: March 4, 2026, 7:29 p.m.