Triple
T18942625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Samueli |
E463423
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Samueli |
—
|
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: Samueli | Statement: [Henry Samueli, familyName, Samueli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samueli Context triple: [Henry Samueli, familyName, Samueli]
-
A.
Samueli
chosen
Samueli is a surname most prominently associated with American engineer and philanthropist Henry Samueli, co-founder of Broadcom Corporation.
-
B.
Samor
Samor is a regional dialect of the Tugen language spoken by the Tugen people of Kenya.
-
C.
Salemi
Salemi is a historic hill town in western Sicily, Italy, known for its medieval center, traditional festivals, and surrounding vineyards and olive groves.
-
D.
Samiyam
Samiyam is an American hip-hop producer and beatmaker known for his off-kilter, synth-heavy instrumentals and association with the Los Angeles beat scene.
-
E.
Sambon
Sambon was a zoologist and parasitologist known for his taxonomic work on parasitic organisms, including naming the human blood fluke Schistosoma mansoni.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3ec857081908da0f974604f2c65 |
completed | April 20, 2026, 7:21 a.m. |
Created at: April 10, 2026, 11:59 a.m.