Triple
T2871167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhône |
E63564
|
entity |
| Predicate | bordersDepartment |
P224
|
FINISHED |
| Object | Ain |
E57120
|
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: Ain | Statement: [Rhône, bordersDepartment, Ain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ain Context triple: [Rhône, bordersDepartment, Ain]
-
A.
Ain
chosen
Ain is a department in eastern France known for its diverse landscapes, historic towns, and proximity to both the Alps and the Swiss border.
-
B.
Aikin
Aikin is the family name of the prominent 18th–19th century English literary and intellectual family to which writer and educator Anna Laetitia Barbauld belonged.
-
C.
Nain
Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
-
D.
Aldan
Aldan is a mining town in Russia’s Sakha Republic known for its significant gold deposits and remote Siberian location.
-
E.
Alnôba
Alnôba is an Indigenous Algonquian language traditionally spoken by the Western Abenaki people of northeastern North America.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfe2dcb48190a194253e733d14af |
completed | March 7, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01db01d348190945ab982ce5c5b2d |
completed | March 10, 2026, 1:33 p.m. |
Created at: March 6, 2026, 10:02 p.m.