Triple
T6679719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tübingen |
E151945
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Ammer
The Ammer is a small river in the German state of Baden-Württemberg that flows through the university town of Tübingen and into the Neckar.
|
E611658
|
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: Ammer | Statement: [Tübingen, hasRiver, Ammer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ammer Context triple: [Tübingen, hasRiver, Ammer]
-
A.
Ammer
The Ammer is a river in Bavaria, Germany, known for flowing through the Ammergau Alps and feeding the Ammersee.
-
B.
Hamme
Hamme is a municipality in East Flanders, Belgium, known for its location along the Scheldt River and its blend of residential areas and natural landscapes.
-
C.
Anmer
Anmer is a small rural village in Norfolk, England, notable for its proximity to the Sandringham Estate and its historic parish church.
-
D.
Amarar
Amarar is the native name used by the Beja people to refer to themselves or their community.
-
E.
Naunhof
Naunhof is a small town in the Free State of Saxony in eastern Germany, known for its surrounding lakes and forests near the city of Leipzig.
- 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: Ammer Triple: [Tübingen, hasRiver, Ammer]
Generated description
The Ammer is a small river in the German state of Baden-Württemberg that flows through the university town of Tübingen and into the Neckar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ammer Target entity description: The Ammer is a small river in the German state of Baden-Württemberg that flows through the university town of Tübingen and into the Neckar.
-
A.
Ammer
The Ammer is a river in Bavaria, Germany, known for flowing through the Ammergau Alps and feeding the Ammersee.
-
B.
Hamme
Hamme is a municipality in East Flanders, Belgium, known for its location along the Scheldt River and its blend of residential areas and natural landscapes.
-
C.
Anmer
Anmer is a small rural village in Norfolk, England, notable for its proximity to the Sandringham Estate and its historic parish church.
-
D.
Amarar
Amarar is the native name used by the Beja people to refer to themselves or their community.
-
E.
Naunhof
Naunhof is a small town in the Free State of Saxony in eastern Germany, known for its surrounding lakes and forests near the city of Leipzig.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b11df8d88190bf19fcb4e7a0bdb3 |
completed | March 27, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7a9fda4819096d4bd3e8133cecb |
completed | March 27, 2026, 9:33 p.m. |
| NEDg | Description generation | batch_69c6f8b1e1f48190bc9058a8a21a4a62 |
completed | March 27, 2026, 9:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f9441d74819098f0639a29fdeb5e |
completed | March 27, 2026, 9:40 p.m. |
Created at: March 27, 2026, 2:03 p.m.