Triple
T21287029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicama Valley |
E524688
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Ascope |
—
|
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: Ascope | Statement: [Chicama Valley, hasSettlement, Ascope]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ascope Context triple: [Chicama Valley, hasSettlement, Ascope]
-
A.
Ascope
chosen
Ascope is a town and provincial capital in northern Peru’s La Libertad Region, known for its agricultural surroundings and role in regional administration.
-
B.
K-Scope
K-Scope is a song by British trip hop band Tricky, known for its dark, atmospheric production and influential use in later hip hop sampling.
-
C.
Arcore
Arcore is a small town in the Lombardy region of northern Italy, known for its historic villas and proximity to Milan.
-
D.
Spektrum
Spektrum is a large indoor arena and event venue in central Oslo, Norway, known for hosting concerts, sports events, and major shows.
-
E.
Arcop
Arcop was a prominent Canadian architectural firm known for its modernist designs and major cultural and institutional projects across Canada.
- 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d717c88190950bd48058912b65 |
completed | April 21, 2026, 8:35 a.m. |
Created at: April 16, 2026, 4:03 p.m.