Triple
T7650745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arne Tiselius |
E173244
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arne |
E148181
|
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: Arne | Statement: [Arne Tiselius, givenName, Arne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arne Context triple: [Arne Tiselius, givenName, Arne]
-
A.
Arne
chosen
Arne is a Scandinavian masculine given name commonly used in Norway, Sweden, and Denmark.
-
B.
Arne
Arne is a novella by Norwegian writer and Nobel laureate Bjørnstjerne Bjørnson, often regarded as a key work in 19th-century Norwegian literature for its portrayal of rural life and psychological depth.
-
C.
Ornes
Ornes is a French village in the Meuse department that was completely destroyed during the Battle of Verdun in World War I and left as an uninhabited memorial site.
-
D.
Arve
The Arve is a river in southwestern Switzerland and southeastern France that flows through Geneva before joining the Rhône.
-
E.
Borge
Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70175e4b88190bc40c839a42180d4 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89ae293148190a30ef03a4a594fe6 |
completed | March 29, 2026, 3:22 a.m. |
Created at: March 27, 2026, 3:58 p.m.