Triple
T13287950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orhan Pamuk |
E316489
|
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 notable abstract painting by British artist Howard Hodgkin, recognized for its expressive brushwork and evocative use of color to suggest memory and atmosphere.
-
C.
Snow
Snow is a common English surname borne by various notable figures in literature, science, and public life.
-
D.
Snow
"Snow" is a song featured on the album *Back to Scratch* by Welsh singer-songwriter Charlotte Church.
-
E.
Snow
"Snow" is a festive song from the 1954 musical film *White Christmas*, celebrated for its nostalgic lyrics about the beauty and romance of wintertime snowfall.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99076aeec8190b0cb883ab60d3f6b |
completed | April 11, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716d4a6f48190a2020e11e887be2e |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:27 p.m.