Triple
T23418516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maxima Sequanorum |
E560577
|
entity |
| Predicate | includedCity |
P8465
|
FINISHED |
| Object | Aventicum |
—
|
NE NERFINISHED |
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: Aventicum | Statement: [Maxima Sequanorum, includedCity, Aventicum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aventicum Context triple: [Maxima Sequanorum, includedCity, Aventicum]
-
A.
Avenches
chosen
Avenches is a historic town in western Switzerland, known for its well-preserved Roman ruins and amphitheater.
-
B.
Allobroges
The Allobroges were an ancient Celtic tribe of Gaul, primarily inhabiting the region between the Rhône River and the Alps in what is now southeastern France.
-
C.
Mediolanum Santonum
Mediolanum Santonum was an important ancient Roman town of the Santones tribe in southwestern Gaul, located in what is now Saintes, France.
-
D.
Murten
Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
-
E.
Tarascon
Tarascon is a historic town in southern France, known for its medieval castle and Provençal heritage along the lower Rhône Valley.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a5438ac08190a40a3d6402794699 |
completed | April 29, 2026, 6:29 a.m. |
Created at: April 17, 2026, 5:40 p.m.