Triple
T14373437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watches and Jewelry |
E356411
|
entity |
| Predicate | brandPortfolioOwner |
P99659
|
FINISHED |
| Object | Zenith |
E356406
|
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: Zenith | Statement: [Watches and Jewelry, brandPortfolioOwner, Zenith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zenith Context triple: [Watches and Jewelry, brandPortfolioOwner, Zenith]
-
A.
Zenith
chosen
Zenith is a Swiss luxury watch manufacturer renowned for its high-precision mechanical movements and chronographs.
-
B.
Zenith
Zenith is a global media agency network specializing in media planning and buying, operating as part of the French advertising and communications conglomerate Publicis Groupe.
-
C.
Mido
Mido is a spelling variant of the name Medo, often used as a given name or nickname in various cultures.
-
D.
Zénith Paris
Zénith Paris is a major indoor concert and events arena in Paris known for hosting large-scale music performances and cultural shows.
-
E.
Zeiger
Zeiger is the birth surname of famed American television and radio host Larry King.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c5514688190be90776c8764d4f3 |
completed | May 8, 2026, 2:37 a.m. |
Created at: April 10, 2026, 1:15 a.m.