Triple
T14376892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tórshavn |
E356497
|
entity |
| Predicate | hasHistoricArea |
P5057
|
FINISHED |
| Object | Reyn |
E1095934
|
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: Reyn | Statement: [Tórshavn, hasHistoricArea, Reyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reyn Context triple: [Tórshavn, hasHistoricArea, Reyn]
-
A.
Reyn
chosen
Reyn is a district within Tórshavn, the capital city of the Faroe Islands, known for its traditional Faroese houses and historic character.
-
B.
Ryen
Ryen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local amenities, and good public transport connections.
-
C.
Renya
Renya Mutaguchi was a Japanese general best known for commanding the ill-fated Imphal campaign in Burma during World War II.
-
D.
Ryn
Ryn is a small historic town in northeastern Poland’s Masurian Lake District, known for its medieval Teutonic castle and lakeside setting.
-
E.
Reyner
Reyner is a masculine given name most notably associated with the British architectural critic and writer Reyner Banham.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900949fc81909be0da1734c46645 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551002948190aeb93d245e1449a7 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:16 a.m.