Triple
T16853497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panasonic Corporation |
E409729
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | National |
E409731
|
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: National | Statement: [Panasonic Corporation, hasBrand, National]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: National Context triple: [Panasonic Corporation, hasBrand, National]
-
A.
National
National is a major centre-right political party in New Zealand, formally known as the New Zealand National Party.
-
B.
National
chosen
National is a Japanese electronics and home appliance brand historically used by Panasonic for a wide range of consumer products, especially in Asian markets.
-
C.
Nacional
Nacional is a news section of the Colombian newspaper El Espectador that focuses on national-level events and issues.
-
D.
Nacional
Nacional is a prominent Uruguayan football club based in Montevideo, known as one of the country's most successful and historic teams.
-
E.
Nacional
Nacional is a character in the 1922 silent drama film "Blood and Sand," which centers on the rise and fall of a celebrated Spanish bullfighter.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37bbb80819086d844a313625cad |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb216fac81909d401c6b9911d1e0 |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.