Triple
T3510153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canal de Garonne |
E74175
|
entity |
| Predicate | crosses |
P416
|
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: [Canal de Garonne, crosses, Agen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agen Context triple: [Canal de Garonne, crosses, Agen]
-
A.
Agen
chosen
Agen is a historic town in southwestern France known for its prunes and location between Bordeaux and Toulouse.
-
B.
Ageo
Ageo is a city in Japan known as a residential and industrial hub within the Greater Tokyo metropolitan area.
-
C.
Agutaynen
Agutaynen is an Austronesian language spoken by the Agutaynen people in the Philippines, primarily in the province of Palawan.
-
D.
Agta
The Agta are an indigenous Negrito people of the Philippines known for their traditionally nomadic, forest-based lifestyle and rich oral traditions.
-
E.
Inagi
Inagi is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama River.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc0e1f0c8190b054d9fba16ce4b3 |
completed | March 8, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373e71ae8819096ea39955c92076a |
completed | March 13, 2026, 2:18 a.m. |
Created at: March 8, 2026, 3:18 p.m.