Triple
T17666530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Lloyd |
E440397
|
entity |
| Predicate | portrayed |
P1668
|
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: [Harry Lloyd, portrayed, Will Scarlett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Scarlett Context triple: [Harry Lloyd, portrayed, 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.
Vizzini
Vizzini is a historic hill town in Sicily, Italy, known for its traditional architecture and its association with the writer Giovanni Verga.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea9d91c81908414ef38c7fb36a4 |
completed | April 19, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02165e842c8190bb28bd8a4b1438ad |
completed | May 11, 2026, 5:48 p.m. |
Created at: April 10, 2026, 9:57 a.m.