Triple
T8061014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weiterstadt |
E188118
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Erzhausen |
E23310
|
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: Erzhausen | Statement: [Weiterstadt, hasNeighboringMunicipality, Erzhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erzhausen Context triple: [Weiterstadt, hasNeighboringMunicipality, Erzhausen]
-
A.
Erzhausen
chosen
Erzhausen is a small municipality in the state of Hesse in central Germany, located near Darmstadt and part of the Rhine-Main metropolitan region.
-
B.
Aegidienberg
Aegidienberg is a district of the town of Bad Honnef in North Rhine-Westphalia, Germany, known for its scenic location in the Siebengebirge region.
-
C.
Hangelsberg
Hangelsberg is a village in the German state of Brandenburg, known as a district of the municipality Grünheide (Mark) in the Oder-Spree region.
-
D.
Steigerwald
Steigerwald is a forested hill range and nature area in northern Bavaria, Germany, known for its beech forests, vineyards, and traditional Franconian landscapes.
-
E.
Hardtberg
Hardtberg is a borough of the German city of Bonn, located in the western part of the city and comprising several residential and administrative districts.
- 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_69ca82b2f68881908c50560697e210da |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3fcc61c0819085edc26e75c5f6d5 |
completed | March 31, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd946a5e188190b2ef0a07a885ade7 |
completed | April 1, 2026, 9:55 p.m. |
Created at: March 30, 2026, 5:26 p.m.