Triple
T2218129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Ford |
E48078
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tom Ford |
E48078
|
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: Tom Ford | Statement: [Tom Ford, name, Tom Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Ford Context triple: [Tom Ford, name, Tom Ford]
-
A.
Tom Ford
chosen
Tom Ford is an American fashion designer and filmmaker known for revitalizing Gucci and directing acclaimed films such as "A Single Man" and "Nocturnal Animals."
-
B.
Karl Lagerfeld
Karl Lagerfeld was a renowned German fashion designer, best known as the longtime creative director of Chanel and a major figure in luxury fashion.
-
C.
Marc Jacobs
Marc Jacobs is an influential American fashion designer known for his eponymous label and former role as creative director at Louis Vuitton.
-
D.
Oscar de la Renta
Oscar de la Renta was a renowned Dominican-American fashion designer celebrated for his elegant, feminine couture and eveningwear, dressing numerous celebrities and first ladies.
-
E.
Valentino
Valentino is a renowned Italian luxury fashion house celebrated for its elegant haute couture, ready-to-wear, and iconic red-carpet designs.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc010bd4c8190ace293b37eac1de5 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae655b369c8190a5d12b87401534d7 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:46 p.m.