Triple
T9021217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karmi |
E215727
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object | Ram Karmi |
E41566
|
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: Ram Karmi | Statement: [Karmi, notableBearer, Ram Karmi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ram Karmi Context triple: [Karmi, notableBearer, Ram Karmi]
-
A.
Ramin Ganeshram
Ramin Ganeshram is an American journalist, food writer, and author known for her work on culinary history and cultural heritage.
-
B.
Rami Shakarchi
Rami Shakarchi is a mathematician and educator best known for coauthoring with Elias Stein a widely used series of graduate-level textbooks on analysis.
-
C.
Dov Karmi
chosen
Dov Karmi was a prominent Israeli architect known for helping shape the modernist architectural landscape of Tel Aviv and other parts of Israel in the mid-20th century.
-
D.
J.R. Rotem
J.R. Rotem is a South African-born American record producer and songwriter known for crafting pop and hip-hop hits for artists such as Rihanna, Jason Derulo, and Sean Kingston.
-
E.
Deepak Nayyar
Deepak Nayyar is an Indian economist and academic known for his work on development economics and his leadership roles in major universities and international economic institutions.
- 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_69ca83a38aa88190bf1bb80c4548b5e2 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a43add08190983b7ac88576fd7e |
completed | April 1, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfeb7a95a88190a41ba5549f2b2d5a |
completed | April 3, 2026, 4:31 p.m. |
Created at: March 30, 2026, 7:07 p.m.