Triple
T14287212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kasaavin |
E354205
|
entity |
| Predicate | appearsInEpisode |
P795
|
FINISHED |
| Object | Spyfall: Part One |
E71118
|
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: Spyfall: Part One | Statement: [Kasaavin, appearsInEpisode, Spyfall: Part One]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spyfall: Part One Context triple: [Kasaavin, appearsInEpisode, Spyfall: Part One]
-
A.
Spyfall
chosen
Spyfall is a two-part Doctor Who television story featuring the Thirteenth Doctor facing a global conspiracy involving mysterious alien beings and the return of the Master.
-
B.
Single Spies
Single Spies is a play by British writer Alan Bennett that dramatizes episodes from the lives of Cambridge spies Guy Burgess and Anthony Blunt with his characteristic blend of wit and political insight.
-
C.
Spies Like Us
Spies Like Us is a 1985 Cold War comedy film starring Dan Aykroyd and Chevy Chase as inept government agents sent on a bogus espionage mission.
-
D.
SPY
SPY is the SPDR S&P 500 ETF, a widely traded fund that tracks the performance of the S&P 500 stock market index.
-
E.
Spies
Spies is a novel by Michael Frayn that explores childhood memory, secrecy, and the blurred line between imagination and reality in wartime England.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de698023288190b1d705235c2b2ca3 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd467f3b3081908261261301674c4e |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:11 a.m.