Triple
T600170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rita R. Colwell |
E11474
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Colwell |
E11474
|
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: Colwell | Statement: [Rita R. Colwell, familyName, Colwell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colwell Context triple: [Rita R. Colwell, familyName, Colwell]
-
A.
Colwell
chosen
Colwell is a surname most notably associated with Rita R. Colwell, an influential American microbiologist and former director of the U.S. National Science Foundation.
-
B.
Nourse
Nourse is a surname and variant spelling of "Nurse," historically associated with English-speaking families and occasionally used as a place or business name.
-
C.
Cresco
Cresco is a small city in northeastern Iowa known for its agricultural community and historic architecture.
-
D.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
E.
Valley Wells
Valley Wells is a small locality situated within California’s Mojave Desert, known primarily as a remote desert community along major regional travel routes.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d78c0f08190b83ad89062ccb0b9 |
completed | March 1, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a51f37f8748190bff705fd2bbc489c |
completed | March 2, 2026, 5:25 a.m. |
Created at: March 1, 2026, 7:35 p.m.