Triple
T14727897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double Up |
E345990
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Sweet Tooth |
E899443
|
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: Sweet Tooth | Statement: [Double Up, hasTrack, Sweet Tooth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sweet Tooth Context triple: [Double Up, hasTrack, Sweet Tooth]
-
A.
Sweet Tooth
Sweet Tooth is a 2012 espionage novel by Ian McEwan that blends Cold War spy intrigue with a metafictional love story set in 1970s Britain.
-
B.
Sweet Tooth
chosen
Sweet Tooth is a fantasy drama television series based on the DC comic about a post-apocalyptic world where human-animal hybrid children emerge following a devastating pandemic.
-
C.
White Tooth
White Tooth is the English meaning of the name "Dent Blanche," a prominent mountain in the Pennine Alps of Switzerland.
-
D.
The Tooth
"The Tooth" is a short story by Shirley Jackson, included in her collection *The Lottery and Other Stories*, that blends psychological unease with elements of the uncanny.
-
E.
Jawbreaker
"Jawbreaker" is a 1999 dark comedy film about a high school clique whose cruel birthday prank accidentally kills their friend, leading to blackmail, cover-ups, and social chaos.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26179688190ba9f3cd045da0e2a |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf099eaf48190b89032b6ac769e67 |
completed | May 8, 2026, 2:18 p.m. |
Created at: April 10, 2026, 1:29 a.m.