Triple
T521751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garonne |
E10830
|
entity |
| Predicate | cityOnRiver |
P165
|
FINISHED |
| Object | Agen |
E64826
|
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: Agen | Statement: [Garonne, cityOnRiver, Agen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agen Context triple: [Garonne, cityOnRiver, Agen]
-
A.
Agen
chosen
Agen is a historic town in southwestern France known for its prunes and location between Bordeaux and Toulouse.
-
B.
Daza
The Daza are an ethnic group of the central Sahara, primarily in Chad, known for their nomadic pastoralist lifestyle and close cultural and linguistic ties to the Toubou (Tebu) peoples.
-
C.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
D.
Ain
Ain is a department in eastern France known for its diverse landscapes, historic towns, and proximity to both the Alps and the Swiss border.
-
E.
Anif
Anif is a small Austrian municipality near Salzburg, known for its historic castle and as a residence of notable figures.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b372408190b3918fec45444674 |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4ab1f95cc8190a6e2dfc3636110b5 |
completed | March 1, 2026, 9:09 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.