Triple
T2976976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orhan Pamuk |
E80421
|
entity |
| Predicate | notableWork |
P4
|
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: [Orhan Pamuk, notableWork, Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snow Context triple: [Orhan Pamuk, notableWork, 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.
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.
-
D.
Frost
Frost is a common English surname borne by numerous notable individuals, including the American poet Robert Frost.
-
E.
Frost
Frost is the middle name of George F. Kennan, the influential American diplomat and historian known for shaping the U.S. Cold War containment strategy.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad998c589c8190b4530f3fb8975187 |
completed | March 8, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b108ecef788190ad40dba81f1036c6 |
completed | March 11, 2026, 6:17 a.m. |
Created at: March 8, 2026, 2:58 p.m.