Triple
T18255028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palantir Technologies Inc. |
E437202
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Stephen Cohen |
—
|
NE NERFINISHED |
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: Stephen Cohen | Statement: [Palantir Technologies Inc., foundedBy, Stephen Cohen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Cohen Context triple: [Palantir Technologies Inc., foundedBy, Stephen Cohen]
-
A.
Stephen Cohen
chosen
Stephen Cohen is a technology entrepreneur best known as a co-founder of the data analytics company Palantir Technologies.
-
B.
Bruce Cohen
Bruce Cohen is an American film and television producer best known for his work on acclaimed films such as "American Beauty" and "Silver Linings Playbook."
-
C.
Andrew Cohen
Andrew Cohen is an entrepreneur best known as a founder of the wireless technology company Qualcomm.
-
D.
Andrew Cohen
Andrew Cohen is a theoretical physicist known for his work in particle physics and for being one of Howard Georgi’s prominent students.
-
E.
Andrew Cohen
Andrew Cohen is a film editor known for his work on the action thriller "Deadly Impact."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd84b3a481908bbc1a5e5034d397 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:34 a.m.