Triple
T12373058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dylan Smith |
E295050
|
entity |
| Predicate | coFounderWith |
P2835
|
FINISHED |
| Object | Sam Ghods |
E292744
|
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: Sam Ghods | Statement: [Dylan Smith, coFounderWith, Sam Ghods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Ghods Context triple: [Dylan Smith, coFounderWith, Sam Ghods]
-
A.
Sam Ghods
chosen
Sam Ghods is a technology entrepreneur best known as a co-founder of the cloud content management company Box.
-
B.
Sam Asghari
Sam Asghari is an Iranian-American fitness trainer, model, and actor best known for his high-profile relationship and marriage to pop star Britney Spears.
-
C.
Ramin Golestanian
Ramin Golestanian is an Iranian-German physicist known for his pioneering work in soft matter and active matter physics, particularly in the theory of microswimmers and nonequilibrium systems.
-
D.
Navid Kermani
Navid Kermani is a German writer, orientalist, and public intellectual known for his essays and novels exploring Islam, European culture, and intercultural dialogue.
-
E.
Kevin Nazemi
Kevin Nazemi is an American entrepreneur best known as a co-founder of the health insurance startup Oscar Health.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa7c9ec81908c685612994543e3 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ac1e82c8190abb46ca5799e6680 |
completed | May 2, 2026, 4:48 p.m. |
Created at: April 8, 2026, 9:54 p.m.