Triple
T1774776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharp X68000 |
E38952
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Sharp Corporation |
E79661
|
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: Sharp Corporation | Statement: [Sharp X68000, manufacturer, Sharp Corporation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sharp Corporation Context triple: [Sharp X68000, manufacturer, Sharp Corporation]
-
A.
Sharp Corporation
chosen
Sharp Corporation is a Japanese multinational electronics manufacturer known for its consumer electronics, display technologies, and home appliances.
-
B.
Tokyo Tsushin Kogyo
Tokyo Tsushin Kogyo was the original name of the Japanese electronics company that later became globally known as Sony.
-
C.
Toshiba
Toshiba is a major Japanese multinational conglomerate known for its electronics, semiconductors, and information technology products and services.
-
D.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
-
E.
Tokyu Corporation
Tokyu Corporation is a major Japanese private railway and real estate company based in Tokyo, known for operating extensive rail networks and developing commercial and residential areas, particularly around Shibuya.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64b6c4a88190ab2f75c8d4814f11 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9982d208190b0c29ee1141e91b0 |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.