Triple
T12406295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bovenden |
E296395
|
entity |
| Predicate | hasMunicipalPart |
P84684
|
FINISHED |
| Object |
Billingshausen
Billingshausen is a village in Lower Saxony, Germany, that forms part of the municipality of Bovenden in the district of Göttingen.
|
E980781
|
NE FINISHED |
How this triple was built (4 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: Billingshausen | Statement: [Bovenden, hasMunicipalPart, Billingshausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billingshausen Context triple: [Bovenden, hasMunicipalPart, Billingshausen]
-
A.
Dannhauser
Dannhauser is a small town and local municipality in KwaZulu-Natal, South Africa, known historically for coal mining and agriculture.
-
B.
Braunshardt
Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
-
C.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
D.
Langhans
Langhans is a German surname most notably associated with Carl Gotthard Langhans, the architect of Berlin’s Brandenburg Gate.
-
E.
Billens-Hennens
Billens-Hennens is a small municipality in the canton of Fribourg in western Switzerland, known for its rural character and location within the Glâne District.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Billingshausen Triple: [Bovenden, hasMunicipalPart, Billingshausen]
Generated description
Billingshausen is a village in Lower Saxony, Germany, that forms part of the municipality of Bovenden in the district of Göttingen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Billingshausen Target entity description: Billingshausen is a village in Lower Saxony, Germany, that forms part of the municipality of Bovenden in the district of Göttingen.
-
A.
Dannhauser
Dannhauser is a small town and local municipality in KwaZulu-Natal, South Africa, known historically for coal mining and agriculture.
-
B.
Braunshardt
Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
-
C.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
D.
Langhans
Langhans is a German surname most notably associated with Carl Gotthard Langhans, the architect of Berlin’s Brandenburg Gate.
-
E.
Billens-Hennens
Billens-Hennens is a small municipality in the canton of Fribourg in western Switzerland, known for its rural character and location within the Glâne District.
- F. None of above. chosen
Provenance (5 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d48f1908190918551c794f98fe3 |
completed | April 10, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63488cac08190a81b2151c827932e |
completed | May 2, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69f635997b088190b6207fcac5594eb2 |
completed | May 2, 2026, 5:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f636d727a08190882eec3fd664b64d |
completed | May 2, 2026, 5:39 p.m. |
Created at: April 8, 2026, 9:55 p.m.