Triple
T5035439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth |
E113408
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Elisabet |
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: Elisabet | Statement: [Elisabeth, hasVariant, Elisabet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elisabet Context triple: [Elisabeth, hasVariant, Elisabet]
-
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.
Elisabeta
Elisabeta is a given name used in various European languages, corresponding to the English name Elizabeth.
-
D.
Maria Christina
Maria Christina, known as Princess Christina of the Netherlands, was a Dutch royal and youngest daughter of Queen Juliana and Prince Bernhard who became known for her work as a singer and music educator.
-
E.
Sophia of Sweden
Sophia of Sweden was a 16th-century Swedish princess, daughter of King Gustav I, known for her troubled marriage and mental health issues within the Vasa dynasty.
- 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_69bea479f01c8190a84ff4973845eb17 |
completed | March 21, 2026, 2 p.m. |
Created at: March 20, 2026, 1:36 p.m.