Triple
T14758954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seiko Noda |
E346804
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Seiko |
E232515
|
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: Seiko | Statement: [Seiko Noda, givenName, Seiko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seiko Context triple: [Seiko Noda, givenName, Seiko]
-
A.
Seiko
chosen
Seiko is a Japanese given name commonly used for women and borne by various notable figures in politics, entertainment, and sports.
-
B.
Seiko Group
Seiko Group is a Japanese corporate group best known for its Seiko brand of watches, clocks, and precision instruments.
-
C.
Longines
Longines is a Swiss luxury watchmaker renowned for its elegant timepieces and long-standing association with equestrian sports and precision timekeeping.
-
D.
Tissot
Tissot is a Swiss watchmaker renowned for its affordable yet high-quality timepieces and long heritage in traditional and sports-oriented horology.
-
E.
Oris
Oris is the given name of O.P. Van Sweringen, one of the Van Sweringen brothers known for their influential real estate and railroad developments in early 20th-century Cleveland, Ohio.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f0f5a48190af008352c26574d7 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cefb7c08190bf69b15165f046d0 |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:30 a.m.