Triple
T9029078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvania Electric Products |
E216121
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Sylvania |
E773493
|
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: Sylvania | Statement: [Sylvania Electric Products, knownAs, Sylvania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvania Context triple: [Sylvania Electric Products, knownAs, Sylvania]
-
A.
Sylvania
Sylvania is a fictional European country best known as the rival nation in the Marx Brothers film "Duck Soup."
-
B.
Sylvania
Sylvania is a suburban city in northwest Ohio, known for its residential communities, parks, and proximity to Toledo.
-
C.
Sylvania
chosen
Sylvania is a long-established lighting and electronics brand known for its consumer and professional light bulbs, fixtures, and related electrical products.
-
D.
Natone
Natone was the original company name of Neutrogena, a well-known American skincare and cosmetics brand.
-
E.
Mathison
Mathison is a surname most notably associated with American screenwriter Melissa Mathison, known for writing the screenplay for "E.T. the Extra-Terrestrial."
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a9bcb508190b58751f1772407d4 |
completed | April 1, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfeb83e8988190bf29baa1aff11ac0 |
completed | April 3, 2026, 4:32 p.m. |
Created at: March 30, 2026, 7:08 p.m.