Triple
T3362823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FX Productions |
E70762
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Snowfall |
E345561
|
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: Snowfall | Statement: [FX Productions, notableWork, Snowfall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowfall Context triple: [FX Productions, notableWork, Snowfall]
-
A.
Snowfall
chosen
Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
-
B.
Thunder Snow
Thunder Snow is a prominent Irish-bred Thoroughbred racehorse best known for winning back-to-back Dubai World Cups in 2018 and 2019.
-
C.
White as Snow
"White as Snow" is a reflective, spiritually themed song by the Irish rock band U2 from their album "No Line on the Horizon."
-
D.
Snowman
Snowman is the post-apocalyptic survivor and narrator of Margaret Atwood’s dystopian novel "Oryx and Crake," through whose perspective the story’s ruined world and its origins are revealed.
-
E.
Avalanche
Avalanche is a decentralized smart contracts platform and blockchain network known for its high throughput, low latency, and support for multiple interoperable subnets.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb26a5a508190948932769de0dbb3 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b32549eb9c81908c3a525da9eab0aa |
completed | March 12, 2026, 8:42 p.m. |
Created at: March 8, 2026, 3:13 p.m.