Triple
T10455097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munster |
E246530
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Fecht |
E516405
|
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: Fecht | Statement: [Munster, locatedOnRiver, Fecht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fecht Context triple: [Munster, locatedOnRiver, Fecht]
-
A.
Fecht
chosen
Fecht is a river in northeastern France that flows through the Alsace region before joining the Ill.
-
B.
Longsword
Longsword is a medieval European sword characterized by its long, straight double-edged blade and two-handed grip, commonly used from the late Middle Ages into the Renaissance.
-
C.
Fleurus
Fleurus is a town in Wallonia, Belgium, historically notable as the site of several major European battles.
-
D.
Wolfenschiessen
Wolfenschiessen is a Swiss municipality in the alpine canton of Nidwalden, known for its mountainous landscape and rural character.
-
E.
Machetá
Machetá is a municipality and town in the Cundinamarca Department of Colombia, located in the Andean highlands northeast of Bogotá.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe48d15c8190bae0d4859e6cda5d |
completed | April 7, 2026, 12:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87f10b45c81908f1d3128c65750f8 |
completed | April 10, 2026, 4:39 a.m. |
Created at: April 6, 2026, 12:18 p.m.