Triple
T16830138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Annecy |
E409125
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ugine |
E1012289
|
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: Ugine | Statement: [Arrondissement of Annecy, contains, Ugine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ugine Context triple: [Arrondissement of Annecy, contains, Ugine]
-
A.
Ugine
chosen
Ugine is a commune in the Savoie department of southeastern France, situated in the Alps and known for its steel industry.
-
B.
Dolomieu
Dolomieu is a commune in the Isère department of southeastern France, known as the birthplace of mathematician Élie Cartan.
-
C.
Reuss
Reuss is a German noble family name historically associated with various princely lines in the region of Thuringia.
-
D.
Tergnier
Tergnier is a commune in northern France known historically as a significant railway junction and industrial town in the Aisne department.
-
E.
Lepechin
Lepechin was an 18th-century Russian naturalist and explorer known for his extensive zoological and botanical studies across the Russian Empire.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b316acc881909c686add53d72388 |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b2a2a5348190b14af8ab88a281b7 |
completed | May 10, 2026, 4:30 p.m. |
Created at: April 10, 2026, 5:23 a.m.