Triple
T13306646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand Cohn |
E316951
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cohn |
E464231
|
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: Cohn | Statement: [Ferdinand Cohn, familyName, Cohn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cohn Context triple: [Ferdinand Cohn, familyName, Cohn]
-
A.
Cohn
chosen
Cohn is a surname most prominently associated with Harry Cohn, the influential co-founder and longtime head of Columbia Pictures.
-
B.
Cohen
Cohen is a common Jewish surname of Hebrew origin historically associated with priestly lineage.
-
C.
Cohon
Cohon is the family surname of American actor, author, and narrator Peter Coyote, born Peter Cohon.
-
D.
Cohen-Kagan
Cohen-Kagan is a Hebrew-language surname most notably borne by Israeli politician and women's rights activist Rachel Cohen-Kagan.
-
E.
Kohn
Kohn is a surname shared by various notable individuals across fields such as science, arts, and public life.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990a8be108190bad0021f95ce3a93 |
completed | April 11, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716e3617081909eea9989cf5e7b30 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:29 p.m.