Triple
T3194661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derek Kolstad |
E66905
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Derek |
E80773
|
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: Derek | Statement: [Derek Kolstad, givenName, Derek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Derek Context triple: [Derek Kolstad, givenName, Derek]
-
A.
Derek
chosen
Derek is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
-
B.
Derek Charles
Derek Charles is the successful corporate executive whose life unravels when he becomes the target of a coworker’s dangerous obsession in the 2009 thriller film "Obsessed."
-
C.
Derek Bond
Derek Bond was a British actor known for his work in mid-20th-century film, television, and theatre.
-
D.
Derek Bryceson
Derek Bryceson was a British-born Tanzanian politician and conservationist who served as director of Tanzania’s national parks and played a key role in supporting Jane Goodall’s chimpanzee research.
-
E.
Derrick
Derrick is the given name of Derrick Rose, an American professional basketball player and former NBA MVP.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada714dbcc8190a7ad21b3c957f151 |
completed | March 8, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bae63688190b2a1a1dba8b2cffa |
completed | March 12, 2026, 5:14 a.m. |
Created at: March 8, 2026, 3:07 p.m.