Triple
T17257923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikhail Vrubel |
E418930
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Pan |
E19364
|
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: Pan | Statement: [Mikhail Vrubel, notableWork, Pan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pan Context triple: [Mikhail Vrubel, notableWork, Pan]
-
A.
Pan
Pan is a genus of great apes that includes chimpanzees and bonobos, our closest living evolutionary relatives.
-
B.
Pan
Pan is a 1894 novel by Norwegian author Knut Hamsun, known for its lyrical portrayal of nature and its psychologically intense depiction of love and jealousy.
-
C.
Pan
Pan is a former member of the American rock band Black Veil Brides, known for their theatrical style and blend of glam metal and post-hardcore.
-
D.
Pan
Pan is a 2015 fantasy adventure film that serves as an origin story for J.M. Barrie’s Peter Pan, reimagining how the boy who wouldn’t grow up first came to Neverland.
-
E.
Pan
chosen
Pan is the rustic Greek god of shepherds, flocks, and wild nature, often depicted with goat-like features and associated with music and untamed wilderness.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6dde4881908e7fc01fd5364616 |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170ff6818819090077dc4a7b774ae |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.