Triple
T4290418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Hood: Prince of Thieves |
E97374
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Will Scarlett |
E15716
|
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: Will Scarlett | Statement: [Robin Hood: Prince of Thieves, mainCharacter, Will Scarlett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Scarlett Context triple: [Robin Hood: Prince of Thieves, mainCharacter, Will Scarlett]
-
A.
Will Scarlet
chosen
Will Scarlet is a legendary member of Robin Hood’s Merry Men, often portrayed as a dashing, hot-headed outlaw skilled with the sword.
-
B.
Madmartigan
Madmartigan is a roguish but heroic swordsman from the fantasy film "Willow," known for his daring exploits and eventual role as a key ally in the fight against Queen Bavmorda.
-
C.
Cad Bane
Cad Bane is a ruthless Duros bounty hunter from the Star Wars universe, renowned for his cunning, advanced weaponry, and frequent clashes with Jedi and other underworld figures.
-
D.
Vizzini
Vizzini is a cunning but overconfident Sicilian criminal mastermind and kidnapper in the fantasy adventure film and novel "The Princess Bride."
-
E.
Lennox Cato
Lennox Cato is a British antiques dealer and television expert best known for his appearances on the BBC’s "Antiques Roadshow."
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3507efb28819091a9d5b9161a5008 |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5db874fb08190974a85cc139b020b |
completed | March 14, 2026, 10:04 p.m. |
Created at: March 12, 2026, 11:08 p.m.