Triple
T5852976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wernigerode |
E130080
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object |
Holtemme
The Holtemme is a small river in the Harz region of Saxony-Anhalt, Germany, flowing through towns such as Wernigerode before joining the Bode.
|
E550185
|
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: Holtemme | Statement: [Wernigerode, locatedOnRiver, Holtemme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holtemme Context triple: [Wernigerode, locatedOnRiver, Holtemme]
-
A.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
B.
Molenstad
Molenstad is the Dutch nickname for the town of Winschoten, referring to its notable association with windmills.
-
C.
Holthees
Holthees is a small village in the Dutch province of North Brabant, known for its rural character and historic church.
-
D.
Hedesunda
Hedesunda is a small locality in east-central Sweden known for its rural character and proximity to forests, lakes, and the Dalälven River.
-
E.
Staaken
Staaken is a locality in western Berlin, Germany, known for its residential areas and historical role as part of the Spandau district near the former inner-German border.
- 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: Holtemme Triple: [Wernigerode, locatedOnRiver, Holtemme]
Generated description
The Holtemme is a small river in the Harz region of Saxony-Anhalt, Germany, flowing through towns such as Wernigerode before joining the Bode.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Holtemme Target entity description: The Holtemme is a small river in the Harz region of Saxony-Anhalt, Germany, flowing through towns such as Wernigerode before joining the Bode.
-
A.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
B.
Molenstad
Molenstad is the Dutch nickname for the town of Winschoten, referring to its notable association with windmills.
-
C.
Holthees
Holthees is a small village in the Dutch province of North Brabant, known for its rural character and historic church.
-
D.
Hedesunda
Hedesunda is a small locality in east-central Sweden known for its rural character and proximity to forests, lakes, and the Dalälven River.
-
E.
Staaken
Staaken is a locality in western Berlin, Germany, known for its residential areas and historical role as part of the Spandau district near the former inner-German border.
- 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_69c0084de39081909eb34e6bed74215a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0355038008190bf38980349b533e2 |
completed | March 22, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1b8f8508190942ce1725884d254 |
completed | March 23, 2026, 2:13 a.m. |
| NEDg | Description generation | batch_69c0a30d66088190b6e37a95527b273d |
completed | March 23, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0a364931c81908d595d74cb4f9a7b |
completed | March 23, 2026, 2:20 a.m. |
Created at: March 22, 2026, 3:55 p.m.