Triple
T520924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Merkel |
E10812
|
entity |
| Predicate | hasMiddleName |
P143
|
FINISHED |
| Object | Dorothea |
E10813
|
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: Dorothea | Statement: [Angela Merkel, hasMiddleName, Dorothea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dorothea Context triple: [Angela Merkel, hasMiddleName, Dorothea]
-
A.
Dorothea
chosen
Dorothea is the middle name of Angela Merkel, the long-serving former chancellor of Germany.
-
B.
Louise
Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
-
C.
Bathsheba
Bathsheba is a prominent biblical figure known as the wife of King David and the mother of King Solomon.
-
D.
Sophia Julian
Sophia Julian was the wife of prominent American labor leader Samuel Gompers and a supportive figure in his personal and family life.
-
E.
Sophia
Sophia of the Palatinate was a 17th-century German princess and Electress of Hanover, best known as the mother of King George I of Great Britain and a key figure in the Protestant succession to the British throne.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1a1817c8190a6cc8f423071d3ad |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a7005ff08190870f19550ede4ee3 |
completed | March 1, 2026, 8:52 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.