Triple
T10030514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Kors |
E204839
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Kors |
E204839
|
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: Kors | Statement: [Michael Kors, hasSurname, Kors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kors Context triple: [Michael Kors, hasSurname, Kors]
-
A.
Kors
chosen
Kors is the surname of American fashion designer Michael Kors, known for his eponymous luxury brand.
-
B.
Korvel
Korvel is a residential neighborhood in the Dutch city of Tilburg, known for its mix of urban housing, local shops, and multicultural character.
-
C.
Korosten
Korosten is a historic city in northern Ukraine known as a regional railway hub and former center of the ancient Drevlians.
-
D.
Koja
Koja is a coastal district in North Jakarta, Indonesia, known for its dense urban neighborhoods and proximity to the city’s port and industrial areas.
-
E.
Kuresa
Kuresa, also known by the honorific Koorathazhwan, was a prominent 11th-century Sri Vaishnava scholar and chief disciple of the theologian Ramanuja.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde7ec088190845656cc2529c771 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d282351ebc8190b22bf3964823b0ee |
completed | April 5, 2026, 3:39 p.m. |
Created at: March 30, 2026, 8:54 p.m.