Triple
T16428543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frauentor |
E399009
|
entity |
| Predicate | hasNearbyPlace |
P3449
|
FINISHED |
| Object |
Frauentorgraben
Frauentorgraben is a major street and section of the historic defensive moat encircling Nuremberg’s old town in Bavaria, Germany.
|
E1213329
|
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: Frauentorgraben | Statement: [Frauentor, hasNearbyPlace, Frauentorgraben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frauentorgraben Context triple: [Frauentor, hasNearbyPlace, Frauentorgraben]
-
A.
Kreuzlinger Forstgraben
Kreuzlinger Forstgraben is a small watercourse in Bavaria that serves as one of the tributary streams feeding into Lake Starnberg.
-
B.
St. Alban-Graben
St. Alban-Graben is a central street in Basel, Switzerland, known for hosting major cultural institutions and serving as an important urban thoroughfare.
-
C.
Schwarzer Graben
Schwarzer Graben is a small waterway or channel in Germany located near the river island of Hasselwerder.
-
D.
Malita Graben
Malita Graben is a structural depression and hydrocarbon-bearing sub-basin within the offshore Bonaparte Basin of northern Australia.
-
E.
Bärengraben
Bärengraben is a historic bear pit and popular tourist attraction in Bern, Switzerland, where live bears—symbols of the city—have been kept for centuries.
- 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: Frauentorgraben Triple: [Frauentor, hasNearbyPlace, Frauentorgraben]
Generated description
Frauentorgraben is a major street and section of the historic defensive moat encircling Nuremberg’s old town in Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frauentorgraben Target entity description: Frauentorgraben is a major street and section of the historic defensive moat encircling Nuremberg’s old town in Bavaria, Germany.
-
A.
Kreuzlinger Forstgraben
Kreuzlinger Forstgraben is a small watercourse in Bavaria that serves as one of the tributary streams feeding into Lake Starnberg.
-
B.
St. Alban-Graben
St. Alban-Graben is a central street in Basel, Switzerland, known for hosting major cultural institutions and serving as an important urban thoroughfare.
-
C.
Schwarzer Graben
Schwarzer Graben is a small waterway or channel in Germany located near the river island of Hasselwerder.
-
D.
Malita Graben
Malita Graben is a structural depression and hydrocarbon-bearing sub-basin within the offshore Bonaparte Basin of northern Australia.
-
E.
Bärengraben
Bärengraben is a historic bear pit and popular tourist attraction in Bern, Switzerland, where live bears—symbols of the city—have been kept for centuries.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328fc223c8190bbed29907351a6f6 |
completed | April 18, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00458331748190a4bd1c5d2d466e6d |
completed | May 10, 2026, 8:44 a.m. |
| NEDg | Description generation | batch_6a0046ce23948190a2207e5e27493dac |
completed | May 10, 2026, 8:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a004767d1c88190814e83f09383e874 |
completed | May 10, 2026, 8:52 a.m. |
Created at: April 10, 2026, 5:09 a.m.