Triple
T13963852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton of Esch-sur-Alzette |
E335869
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Roeser |
E1056589
|
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: Roeser | Statement: [Canton of Esch-sur-Alzette, containsCity, Roeser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roeser Context triple: [Canton of Esch-sur-Alzette, containsCity, Roeser]
-
A.
Roeser
chosen
Roeser is a commune and small town in southern Luxembourg, situated just south of Luxembourg City in the country’s Minett region.
-
B.
Roderesch
Roderesch is a small village in the municipality of Noordenveld in the province of Drenthe in the northeastern Netherlands.
-
C.
Rutishauser
Rutishauser is a Swiss surname most notably associated with Heinz Rutishauser, a pioneering mathematician and computer scientist in the field of numerical analysis and early programming languages.
-
D.
Riedesel
Riedesel is a German surname historically associated with noble families and notable figures such as military officers and diplomats.
-
E.
Röthlein
Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7e24f08190ba939a8044860033 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac8e47d48190a1d5e841810fe50c |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:18 p.m.