Triple
T21137986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sol Stein |
E520862
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sol |
—
|
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: Sol | Statement: [Sol Stein, givenName, Sol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sol Context triple: [Sol Stein, givenName, Sol]
-
A.
Sol
Sol is the Sun, the G-type main-sequence star at the center of our solar system that provides Earth with light and heat.
-
B.
Sol
Sol is a Mexican-style pale lager beer brand known for its light, refreshing taste and wide international distribution.
-
C.
Sol
Sol is a major central square and transport hub in Madrid, Spain, known as one of the city's busiest public spaces and a symbolic heart of the capital.
-
D.
Sol
chosen
Sol is a masculine given name, often used as a short form of Solomon or as a name meaning "sun" in several languages.
-
E.
Sol
Sol is the first name of Sol C. Siegel, an American film producer known for his work in Hollywood during the mid-20th century.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7235d1c788190a28577a753532b2a |
completed | April 21, 2026, 7:12 a.m. |
Created at: April 16, 2026, 2:57 p.m.