Triple
T4987643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Astrid of Belgium |
E112042
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Astrid |
E112042
|
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: Astrid | Statement: [Astrid of Belgium, givenName, Astrid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Astrid Context triple: [Astrid of Belgium, givenName, Astrid]
-
A.
Astrid
chosen
Astrid is a Belgian princess and member of the country’s royal family.
-
B.
Gisela
Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
-
C.
Elin
Elin is a feminine given name, commonly used in Scandinavian countries and often considered a variant of Ellen or Helen.
-
D.
Agneta
Agneta is a feminine given name, primarily used in Scandinavian countries, that is a variant of the name Agnes.
-
E.
Ingeborg
Ingeborg is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
- 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_69bd441be7bc8190b530362d427b97d2 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd727d473c8190beea66bf11a826e3 |
completed | March 20, 2026, 4:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a20a8f88190980409794c90461f |
completed | March 21, 2026, 12:08 p.m. |
Created at: March 20, 2026, 1:34 p.m.