Triple
T19501104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretel |
E487902
|
entity |
| Predicate | siblingOf |
P363
|
FINISHED |
| Object | Hansel |
—
|
NE NERFINISHED |
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: Hansel | Statement: [Gretel, siblingOf, Hansel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hansel Context triple: [Gretel, siblingOf, Hansel]
-
A.
Hansel
chosen
Hansel is a young boy from the classic fairy tale "Hansel and Gretel," known for his cleverness in trying to outwit a witch after being abandoned in the forest.
-
B.
Hansel & Gretel
Hansel & Gretel is a popular ballet adaptation of the classic Brothers Grimm fairy tale about two siblings who outwit a witch in a magical forest.
-
C.
Holda in Gretel & Hansel
Holda in "Gretel & Hansel" is the sinister witch who lures children to her enchanted forest home and serves as the film’s primary antagonist.
-
D.
Holda
Holda is the witch-like antagonist portrayed by Alice Krige in the 2020 dark fantasy horror film "Gretel & Hansel."
-
E.
Hosaena
Hosaena is a town in southern Ethiopia that serves as an important administrative and commercial center in the Southern Nations, Nationalities, and Peoples' Region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350ce7cc819086d77bbd9cd52b53 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.