Triple
T19918373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afterland |
E478722
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Miles |
—
|
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: Miles | Statement: [Afterland, hasCharacter, Miles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miles Context triple: [Afterland, hasCharacter, Miles]
-
A.
Miles
Miles is a mysterious and possibly corrupted young boy in Henry James's gothic novella "The Turn of the Screw."
-
B.
Miles
Miles are the reward points earned and redeemed by members of the Flying Blue frequent flyer loyalty program.
-
C.
Miles
Miles is a charming, affable film composer portrayed by Jack Black in the romantic comedy "The Holiday."
-
D.
Miles
Miles is a character in the action-thriller television series "The Continental: From the World of John Wick," which explores the criminal underworld surrounding the infamous assassin hotel.
-
E.
Miles
chosen
Miles is the central protagonist of Lauren Beukes’s dystopian novel "Afterland," navigating a post-pandemic world where almost all men have died.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c3d990819089386d9f30323e8c |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.