Triple
T1502133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idina Menzel |
E33817
|
entity |
| Predicate | characterVoiced |
P13156
|
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: [Idina Menzel, characterVoiced, Elsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elsa Context triple: [Idina Menzel, characterVoiced, 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.
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.
-
C.
Olaf
Olaf is a masculine given name of Old Norse origin, commonly used in Germanic and Scandinavian countries.
-
D.
Greta
Greta is a small town located within the Hunter Region of New South Wales, Australia.
-
E.
Greta
Greta is a feminine given name, commonly used as a diminutive or variant of names like Margaret in various European languages.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a8872e41848190b35b37f32aef784f |
completed | March 4, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1cb578e4819082d254462e10e4f0 |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 4, 2026, 7:24 p.m.