Triple
T4059398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ella |
E84771
|
entity |
| Predicate | derivedFrom |
P909
|
FINISHED |
| Object | Elisabeth |
E113408
|
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: Elisabeth | Statement: [Ella, derivedFrom, Elisabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elisabeth Context triple: [Ella, derivedFrom, Elisabeth]
-
A.
Elisabeth
chosen
Elisabeth is a feminine given name of Hebrew origin, commonly used in various European languages as a form of Elizabeth.
-
B.
Elisabeth
Elisabeth is a metro station on the Brussels Metro system in Brussels, Belgium.
-
C.
Louise of Great Britain
Louise of Great Britain was a British princess who became Queen of Denmark and Norway through her marriage to King Frederick V.
-
D.
Mary Adelaide
Mary Adelaide was a British princess of the House of Hanover, mother of Queen Mary and grandmother of King George VI and great-grandmother of Queen Elizabeth II.
-
E.
Anne
Anne is the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbd13b4481908f9c09cc4f4a9724 |
completed | March 9, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b52e31c819099f9d354c197cf00 |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:38 p.m.