Triple
T12799449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralf |
E305974
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Ralph |
unclear NED1
|
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: Ralph | Statement: [Ralf, relatedName, Ralph]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Context triple: [Ralf, relatedName, Ralph]
-
A.
Ralph
Ralph is the given name of Ralph Waldo Emerson, the influential 19th-century American essayist, lecturer, philosopher, and central figure of the Transcendentalist movement.
-
B.
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.
-
C.
Ralph
Ralph is the central protagonist of the film "The Other Man," around whom the story’s primary conflict and emotional drama revolve.
-
D.
Ralph
Ralph is the first name of legendary American NASCAR driver Dale Earnhardt.
-
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. chosen
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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6f858c8190915ede38e9a6a2df |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684e61e7081908dec7958e8bc1125 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:30 p.m.