Triple
T10185990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A39 motorway (France) |
E236908
|
entity |
| Predicate | departmentTraversed |
P42199
|
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: [A39 motorway (France), departmentTraversed, Ain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ain Context triple: [A39 motorway (France), departmentTraversed, 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.
A’aninin
A’aninin, also known as the Gros Ventre, are a Native American people of the Northern Plains historically associated with present-day Montana.
-
C.
Anaa
Anaa is a remote coral atoll in French Polynesia’s Tuamotu Archipelago, known for its large lagoon, traditional Polynesian culture, and historical significance as a former regional center.
-
D.
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.
-
E.
Ayan
Ayan is a 2009 Tamil-language action thriller film starring Suriya, known for its smuggling-centric plot and commercial success.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded790b488190b1ed4645554873cd |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317a4d99c8190941322d3de2998f5 |
completed | April 6, 2026, 2:17 a.m. |
Created at: March 30, 2026, 9:12 p.m.