Triple
T14399223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Bertilak |
E357026
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | the Green Knight |
E67094
|
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: the Green Knight | Statement: [Lord Bertilak, alsoKnownAs, the Green Knight]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: the Green Knight Context triple: [Lord Bertilak, alsoKnownAs, the Green Knight]
-
A.
Green Knight
chosen
The Green Knight is a mysterious, supernatural challenger in Arthurian legend whose beheading game with Sir Gawain tests the knight’s honor and courage.
-
B.
the Black Knight
The Black Knight is the grieving lover in Geoffrey Chaucer’s dream-vision poem "The Book of the Duchess," whose lament over his lost lady reveals the work’s central themes of love and loss.
-
C.
The Black Knight
The Black Knight is a mysterious armored warrior who serves as a formidable antagonist in the 1954 adventure film "Prince Valiant."
-
D.
The Black Knight
The Black Knight is a music producer known for crafting beats and soundscapes, including work on tracks by The Meth Lab.
-
E.
The White Knight
The White Knight is a gentle, eccentric, and chivalrous character in Lewis Carroll’s "Through the Looking-Glass," often interpreted as a self-parody of the author himself.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9083f9d081908fe5c99655c410b3 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551eb09c8190a102ab452371e5b1 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.