Triple
T5035443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth |
E113408
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Elsa |
E44923
|
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: Elsa | Statement: [Elisabeth, hasShortForm, Elsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elsa Context triple: [Elisabeth, hasShortForm, Elsa]
-
A.
Elsa
chosen
Elsa is a feminine given name of Germanic origin, widely recognized today through its use for the main character in Disney's animated film "Frozen."
-
B.
Anna and Elsa
Anna and Elsa are the popular sister protagonists from Disney's animated film "Frozen," known for their roles as the Snow Queen and the princess of Arendelle.
-
C.
Rapunzel
Rapunzel is a classic fairy-tale princess best known for her extraordinarily long hair and her story of captivity in a tower and eventual escape.
-
D.
Helga
Helga is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
-
E.
Elin
Elin is a feminine given name, commonly used in Scandinavian countries and often considered a variant of Ellen or Helen.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73b9ad488190a2a8c4da8858eb91 |
completed | March 20, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c759c608190875b6d48d99024b4 |
completed | March 21, 2026, 1:26 p.m. |
Created at: March 20, 2026, 1:36 p.m.