Triple
T23169307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dale Earnhardt |
E578800
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ralph |
—
|
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: Ralph | Statement: [Dale Earnhardt, givenName, Ralph]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Context triple: [Dale Earnhardt, givenName, Ralph]
-
A.
Ralph
Ralph is a supporting character in the 1984 adventure-romance film "Romancing the Stone," known for his involvement in the story’s treasure-hunting escapades.
-
B.
Ralph
chosen
Ralph is the first name of legendary American NASCAR driver Dale Earnhardt.
-
C.
Ralph
Ralph is a surname of English origin that has been borne by various notable individuals across different fields.
-
D.
Ralph
Ralph is a key imaging and spectrometer instrument aboard NASA’s New Horizons spacecraft, designed to capture detailed visible and infrared observations of distant solar system bodies like Pluto and Kuiper Belt objects.
-
E.
Ralph
Ralph is the given first name of American politician Owen Brewster, who served as a U.S. Senator and Governor of Maine in 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2e5e208190839ec37de4b974af |
completed | April 29, 2026, 4:55 a.m. |
Created at: April 17, 2026, 4:03 p.m.