Triple
T12887122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darmstadt-Dieburg |
E308256
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Griesheim |
E734333
|
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: Griesheim | Statement: [Darmstadt-Dieburg, contains, Griesheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Griesheim Context triple: [Darmstadt-Dieburg, contains, Griesheim]
-
A.
Griesheim
chosen
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
B.
Sulzheim
Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
C.
Ringelheim
Ringelheim is a historic locality in present-day Germany, known as the birthplace of the early medieval noblewoman and later saint Matilda of Ringelheim.
-
D.
Hückeswagen
Hückeswagen is a small historic town in western Germany’s North Rhine-Westphalia, known for its medieval castle and location in the hilly Bergisches Land region.
-
E.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714415c08190aa9944b494a3ddad |
completed | April 10, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c1ee7048190b2571364b25bd49d |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 9, 2026, 5:39 p.m.