Triple
T11317921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunrise, Sunset |
E268012
|
entity |
| Predicate | sungByCharacter |
P14884
|
FINISHED |
| Object | Perchik |
E918845
|
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: Perchik | Statement: [Sunrise, Sunset, sungByCharacter, Perchik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perchik Context triple: [Sunrise, Sunset, sungByCharacter, Perchik]
-
A.
Perchik
chosen
Perchik is a radical young student and one of Tevye’s daughters’ suitors in the musical and film "Fiddler on the Roof," set in the fictional village of Anatevka.
-
B.
Gopchik
Gopchik is a young, resourceful fellow prisoner in Aleksandr Solzhenitsyn’s novel "One Day in the Life of Ivan Denisovich," noted for his adaptability and survival instincts in the labor camp.
-
C.
Pinhas
Pinhas is a masculine given name of Hebrew origin, commonly used in Jewish communities and derived from a biblical figure.
-
D.
Misha
Misha is the bear mascot of the 1980 Moscow Summer Olympics, widely remembered for its iconic, sentimental farewell during the closing ceremony.
-
E.
Tobolowsky
Tobolowsky is the surname of American character actor and storyteller Stephen Tobolowsky, known for his prolific work in film and television.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c3cf748190987838029d9f7fff |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e542f294988190bb456326e4184dcb |
completed | April 19, 2026, 9:02 p.m. |
Created at: April 8, 2026, 9:32 p.m.