Triple
T13879772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marga |
E333681
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Margareta |
E113357
|
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: Margareta | Statement: [Marga, relatedName, Margareta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margareta Context triple: [Marga, relatedName, Margareta]
-
A.
Margareta
chosen
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
B.
Maddalene
Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
-
C.
Anna Margareta
Anna Margareta Tunder was a historical figure known primarily as the namesake and likely relative of the German Baroque composer and organist Franz Tunder.
-
D.
Hjördis
Hjördis is a Scandinavian feminine given name, most notably borne by Swedish model and actress Hjördis Genberg.
-
E.
Agneta
Agneta is a feminine given name, primarily used in Scandinavian countries, that is a variant of the name Agnes.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0be71d388190909290cad2c6daf5 |
completed | April 14, 2026, 9:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac824a60819090894504dbb41de9 |
completed | May 6, 2026, 9:02 p.m. |
Created at: April 9, 2026, 10:15 p.m.