Triple
T17436324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Beard |
E424009
|
entity |
| Predicate | characterAlias |
P41555
|
FINISHED |
| Object | Red Beard |
—
|
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: Red Beard | Statement: [Red Beard, characterAlias, Red Beard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Red Beard Context triple: [Red Beard, characterAlias, Red Beard]
-
A.
Red Beard
Red Beard is the English translation of "Barbarossa," the famous epithet of Holy Roman Emperor Frederick I, referring to his distinctive red facial hair.
-
B.
Red Beard
chosen
Red Beard is a 1965 Japanese period drama film directed by Akira Kurosawa, renowned for its humanistic portrayal of a gruff yet compassionate doctor mentoring a young physician in an Edo-era clinic.
-
C.
Yellowbeard
Yellowbeard is a 1983 British-American pirate comedy film featuring an ensemble cast of prominent comedians, including members of Monty Python and Cheech & Chong.
-
D.
Robin Beard
Robin Beard was an American Republican politician who served as a U.S. Representative from Tennessee from the early 1970s to the early 1980s.
-
E.
Black Phillip
Black Phillip is the sinister goat embodying the Devil in the 2015 horror film "The Witch."
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4490426008190b474ed76aca5d6f3 |
completed | April 19, 2026, 3:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.