Triple
T11124629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roses in the Snow |
E263102
|
entity |
| Predicate | nextWork |
P9710
|
FINISHED |
| Object | Evangeline |
E29535
|
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: Evangeline | Statement: [Roses in the Snow, nextWork, Evangeline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evangeline Context triple: [Roses in the Snow, nextWork, Evangeline]
-
A.
Evangeline
chosen
Evangeline is a narrative poem by Henry Wadsworth Longfellow that tells the tragic story of an Acadian girl's lifelong search for her lost love amid the Great Upheaval.
-
B.
Evangeline
Evangeline is a narrative work—likely a fantasy or historical fiction story—that features the character Basil the blacksmith.
-
C.
Evangeline
Evangeline is a fictional universe centered on the character Benedict Bellefontaine, likely featuring his adventures, relationships, and the world that shapes his story.
-
D.
Evangeline
Evangeline is a music producer known for contributing to the collaborative hip-hop project Kids See Ghosts by Kanye West and Kid Cudi.
-
E.
Evangeline
Evangeline is a feminine given name of Greek origin meaning "bearer of good news," often associated with literary and poetic usage.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7e82e933481908550499cf9dd6531 |
completed | April 9, 2026, 5:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d89378c8190acc7afd1ecdbfbac |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 8, 2026, 9:28 p.m.