Triple
T22545864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adolph Tidemand |
E557421
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Hanna Tidemand |
—
|
NE NERFINISHED |
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: Hanna Tidemand | Statement: [Adolph Tidemand, mother, Hanna Tidemand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanna Tidemand Context triple: [Adolph Tidemand, mother, Hanna Tidemand]
-
A.
Hanna Tidemand
chosen
Hanna Tidemand was the mother of Norwegian romantic nationalist painter Adolph Tidemand, known for his depictions of 19th-century Norwegian rural life.
-
B.
Sofia Levander
Sofia Levander is a Swedish writer and former financial journalist best known as the wife of Spotify co-founder and CEO Daniel Ek.
-
C.
Hannah Roennfeldt
Hannah Roennfeldt is a grieving Australian mother in the novel "The Light Between Oceans," whose lost child becomes central to the story’s moral and emotional conflict.
-
D.
Hannah Fagerbakke
Hannah Fagerbakke is the daughter of American actor and voice actor Bill Fagerbakke.
-
E.
Hanna Alström
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f35b9888190b4e1b50d5097b211 |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.