Triple
T26410525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chanel |
E663946
|
entity |
| Predicate | notableProduct |
P1448
|
FINISHED |
| Object |
Chanel J12 watch
The Chanel J12 watch is a luxury timepiece renowned for its sleek, sporty design and innovative use of high-tech ceramic, which has become an icon in contemporary watchmaking.
|
E1726159
|
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: Chanel J12 watch | Statement: [Chanel, notableProduct, Chanel J12 watch]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chanel J12 watch Triple: [Chanel, notableProduct, Chanel J12 watch]
Generated description
The Chanel J12 watch is a luxury timepiece renowned for its sleek, sporty design and innovative use of high-tech ceramic, which has become an icon in contemporary watchmaking.
Provenance (5 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f6113143f481909c64dfc1975e3a59 |
completed | May 2, 2026, 2:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11aeba42d88190b867fa6279dada9d |
completed | May 23, 2026, 1:42 p.m. |
| NEDg | Description generation | batch_6a11af82fb088190bee576d403827a3e |
completed | May 23, 2026, 1:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11b02a01f4819088f0f84f9ca335af |
completed | May 23, 2026, 1:48 p.m. |
Created at: April 26, 2026, 11:37 p.m.