Triple
T4908890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaretha de Ruyter |
E110181
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Margaretha |
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: Margaretha | Statement: [Margaretha de Ruyter, givenName, Margaretha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaretha Context triple: [Margaretha de Ruyter, givenName, Margaretha]
-
A.
Margareta
chosen
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
B.
Ottla
Ottla was the beloved younger sister of writer Franz Kafka, known from his diaries and letters for her close relationship with him and her tragic death in the Holocaust.
-
C.
Violanta
Violanta is a one-act opera by Erich Wolfgang Korngold, known for its lush late-Romantic score and psychologically intense drama set in Renaissance Venice.
-
D.
Gisela
Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
-
E.
Sorsha
Sorsha is a warrior princess from the fantasy film "Willow" who initially serves her evil mother Queen Bavmorda before ultimately turning against her.
- 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e765094819099481f4f2dd7c47d |
completed | March 20, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fe098b081908e17d6d349b76364 |
completed | March 21, 2026, 10:16 a.m. |
Created at: March 20, 2026, 1:29 p.m.