Triple
T14019600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Unna |
E337292
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Selm |
E992300
|
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: Selm | Statement: [district of Unna, contains, Selm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selm Context triple: [district of Unna, contains, Selm]
-
A.
Selm
chosen
Selm is a small town in the German state of North Rhine-Westphalia, located in the Ruhr area.
-
B.
Eidsberg
Eidsberg is a former municipality and rural town area in southeastern Norway, historically part of Østfold county and known for its agricultural landscape and cultural heritage.
-
C.
Lonsee
Lonsee is a small municipality in the Alb-Donau district of Baden-Württemberg, Germany, situated on the Swabian Jura near the city of Ulm.
-
D.
Balve
Balve is a small town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its limestone caves and scenic Sauerland surroundings.
-
E.
Garmsar
Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f3c7cd88190b236382058581740 |
completed | April 14, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc32d77108190b038e8a750738439 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.