Triple
T8559098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikram (2022 film) |
E202645
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Rolex |
E158011
|
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: Rolex | Statement: [Vikram (2022 film), featuresCharacter, Rolex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rolex Context triple: [Vikram (2022 film), featuresCharacter, Rolex]
-
A.
Rolex
chosen
Rolex is a prestigious Swiss luxury watchmaker renowned worldwide for its high-end timepieces and strong association with elite sports and motorsport events.
-
B.
Longines
Longines is a Swiss luxury watchmaker renowned for its elegant timepieces and long-standing association with equestrian sports and precision timekeeping.
-
C.
Hublot
Hublot is a Swiss luxury watchmaker known for its bold, innovative designs and fusion of traditional watchmaking with modern materials.
-
D.
Baume & Mercier
Baume & Mercier is a Swiss luxury watchmaking brand known for its elegant, classic timepieces and long horological heritage.
-
E.
Ulysse Nardin
Ulysse Nardin is a Swiss luxury watchmaker renowned for its high-end marine chronometers and innovative horological complications.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9485dd88190bc2cf2adf39d48ee |
completed | March 31, 2026, 3:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce894d82588190b558d5b2dc65eafe |
completed | April 2, 2026, 3:20 p.m. |
Created at: March 30, 2026, 6:20 p.m.