Triple
T3728731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snow (novel) |
E79010
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Snow |
E79010
|
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: Snow | Statement: [Snow (novel), title, Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snow Context triple: [Snow (novel), title, Snow]
-
A.
Snow
chosen
"Snow" is a political and philosophical novel by Turkish Nobel laureate Orhan Pamuk that explores identity, secularism, and Islamism in contemporary Turkey.
-
B.
Snow
Snow is a white color variant of the iMac G3, known for its clean, minimalist appearance among the line’s iconic translucent and colorful designs.
-
C.
Snowfall
Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
-
D.
Winter
"Winter" is an episode of the science documentary series *Frozen Planet* that explores how animals and ecosystems survive and adapt during the harsh polar winter.
-
E.
Winter
"Winter" is an 1873 allegorical painting by French artist Pierre Puvis de Chavannes, depicting a serene, muted landscape that embodies the quiet austerity of the winter season.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb17432881909390284b935ed3fd |
completed | March 8, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db13d34881909fa74c682184b797 |
completed | March 14, 2026, 3:50 a.m. |
Created at: March 8, 2026, 3:34 p.m.