Triple
T9653322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elena of Avalor |
E233387
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | Isabel |
E114378
|
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: Isabel | Statement: [Elena of Avalor, hasMainCharacter, Isabel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isabel Context triple: [Elena of Avalor, hasMainCharacter, Isabel]
-
A.
Isabel
chosen
Isabel is a feminine given name of Spanish origin, widely used in Spanish- and Portuguese-speaking countries and borne by numerous notable historical and contemporary figures.
-
B.
Isabel
Isabel is a Spanish historical drama television series centered on the life and reign of Queen Isabella I of Castile.
-
C.
Isabelle
Isabelle is a popular character from the Animal Crossing series who also appears as a playable racer in Mario Kart 8.
-
D.
Isabel Rivers
Isabel Rivers is a central character in the adventure novel "Beau Geste," closely connected to the Geste brothers and their dramatic exploits.
-
E.
Isabella
Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
- 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bb26b748190bc32e2003829b0ec |
completed | April 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18270dee481909c8d2de1fafdaf5b |
completed | April 4, 2026, 9:28 p.m. |
Created at: March 30, 2026, 8:13 p.m.