Triple
T12677876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landshut |
E302865
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Ländtor
Ländtor is a historic city gate in Landshut, Germany, known as one of the town’s most prominent medieval landmarks.
|
E996733
|
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: Ländtor | Statement: [Landshut, hasLandmark, Ländtor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ländtor Context triple: [Landshut, hasLandmark, Ländtor]
-
A.
Harlingerland
Harlingerland is a historic coastal region in East Frisia in northwestern Germany, known for its North Sea landscape, dike systems, and traditional Frisian culture.
-
B.
Töwerland
Töwerland is the poetic nickname for the North Sea island of Juist, known for its tranquil, car-free environment and natural beauty.
-
C.
Orlamünde
Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
-
D.
Dodangaslanda
Dodangaslanda is a rural town and electoral constituency in the Kurunegala District of Sri Lanka.
-
E.
Jorsalle
Jorsalle is a small village in Nepal’s Khumbu region that serves as a common stopover for trekkers on the route to Everest Base Camp.
- 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: Ländtor Triple: [Landshut, hasLandmark, Ländtor]
Generated description
Ländtor is a historic city gate in Landshut, Germany, known as one of the town’s most prominent medieval landmarks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ländtor Target entity description: Ländtor is a historic city gate in Landshut, Germany, known as one of the town’s most prominent medieval landmarks.
-
A.
Harlingerland
Harlingerland is a historic coastal region in East Frisia in northwestern Germany, known for its North Sea landscape, dike systems, and traditional Frisian culture.
-
B.
Töwerland
Töwerland is the poetic nickname for the North Sea island of Juist, known for its tranquil, car-free environment and natural beauty.
-
C.
Orlamünde
Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
-
D.
Dodangaslanda
Dodangaslanda is a rural town and electoral constituency in the Kurunegala District of Sri Lanka.
-
E.
Jorsalle
Jorsalle is a small village in Nepal’s Khumbu region that serves as a common stopover for trekkers on the route to Everest Base Camp.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b1dff48190923290555ece5d89 |
completed | April 10, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671a341288190822fae2469efea09 |
completed | May 2, 2026, 9:50 p.m. |
| NEDg | Description generation | batch_69f672ac07908190bd2dfe90d55a13c1 |
completed | May 2, 2026, 9:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67360b530819085d5db2aa0b7513d |
completed | May 2, 2026, 9:57 p.m. |
Created at: April 9, 2026, 5:20 p.m.