Triple
T5381559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ill |
E113094
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Sélestat |
E57547
|
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: Sélestat | Statement: [Ill, flowsThrough, Sélestat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sélestat Context triple: [Ill, flowsThrough, Sélestat]
-
A.
Sélestat
chosen
Sélestat is a historic town in the Alsace region of northeastern France, known for its well-preserved medieval architecture and cultural heritage.
-
B.
Wissembourg
Wissembourg is a historic town in northeastern France’s Alsace region, known for its well-preserved medieval architecture and proximity to the German border.
-
C.
Kaysersberg
Kaysersberg is a picturesque medieval town in France’s Alsace region, renowned for its half-timbered houses, hillside vineyards, and well-preserved historic charm.
-
D.
Molsheim
Molsheim is a historic town in northeastern France’s Grand Est region, known for its medieval architecture and as the birthplace of the Bugatti automobile brand.
-
E.
Haguenau
Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd86cfe7fc8190bb73c60cae7c927d |
completed | March 20, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3a96fba481909659b13425951068 |
completed | March 22, 2026, 12:40 a.m. |
Created at: March 20, 2026, 2:03 p.m.