Triple
T18273952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kandel Chapel |
E437684
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Kandel
Kandel is a town in the state of Rhineland-Palatinate in southwestern Germany, known for its historic buildings and proximity to the Bienwald forest.
|
E1315542
|
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: Kandel | Statement: [Kandel Chapel, locatedIn, Kandel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kandel Context triple: [Kandel Chapel, locatedIn, Kandel]
-
A.
Kandel
Kandel is a prominent mountain in Germany’s Black Forest region, known for its scenic views and outdoor recreation opportunities.
-
B.
Kahana
Kahana is a variant form of the Jewish surname Cohen, often used in Ashkenazi communities.
-
C.
Harlen
Harlen is the given name of J Harlen Bretz, the American geologist known for his pioneering work on the Missoula Floods and the Channeled Scablands.
-
D.
Dairen
Dairen, now known as Dalian, is a major port city in northeastern China that historically served as an important strategic and commercial hub under various foreign leases and administrations.
-
E.
Sylvania
Sylvania is a fictional European country best known as the rival nation in the Marx Brothers film "Duck Soup."
- 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: Kandel Triple: [Kandel Chapel, locatedIn, Kandel]
Generated description
Kandel is a town in the state of Rhineland-Palatinate in southwestern Germany, known for its historic buildings and proximity to the Bienwald forest.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kandel Target entity description: Kandel is a town in the state of Rhineland-Palatinate in southwestern Germany, known for its historic buildings and proximity to the Bienwald forest.
-
A.
Kandel
Kandel is a prominent mountain in Germany’s Black Forest region, known for its scenic views and outdoor recreation opportunities.
-
B.
Kahana
Kahana is a variant form of the Jewish surname Cohen, often used in Ashkenazi communities.
-
C.
Harlen
Harlen is the given name of J Harlen Bretz, the American geologist known for his pioneering work on the Missoula Floods and the Channeled Scablands.
-
D.
Dairen
Dairen, now known as Dalian, is a major port city in northeastern China that historically served as an important strategic and commercial hub under various foreign leases and administrations.
-
E.
Sylvania
Sylvania is a fictional European country best known as the rival nation in the Marx Brothers film "Duck Soup."
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5005006108190bbddddbe6bbdc911 |
completed | April 19, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03b3fc2a808190be07b43e9e7ac3bb |
completed | May 12, 2026, 11:13 p.m. |
| NEDg | Description generation | batch_6a03b53fc3688190aa6f8e9673763e79 |
completed | May 12, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03b62cb67481908c78ca4d55710dbd |
completed | May 12, 2026, 11:22 p.m. |
Created at: April 10, 2026, 10:34 a.m.