Triple
T17049861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Main-Tauber-Kreis |
E413663
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Assamstadt
Assamstadt is a small municipality in the northeastern part of the German state of Baden-Württemberg.
|
E1248421
|
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: Assamstadt | Statement: [Main-Tauber-Kreis, contains, Assamstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Assamstadt Context triple: [Main-Tauber-Kreis, contains, Assamstadt]
-
A.
Dibrugarh
Dibrugarh is a prominent city in northeastern India known as a major commercial and industrial hub of Assam, especially for its tea industry and oil and natural gas sectors.
-
B.
Chandanagar
Chandanagar is a residential and commercial suburb in the northwestern part of Hyderabad, India, known for its proximity to IT hubs and growing urban infrastructure.
-
C.
Agartala
Agartala is the capital city of the Indian state of Tripura and a major urban and economic center in Northeast India.
-
D.
Guwahati
Guwahati is a major city in northeastern India, serving as a key cultural, economic, and transportation hub for the region.
-
E.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
- 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: Assamstadt Triple: [Main-Tauber-Kreis, contains, Assamstadt]
Generated description
Assamstadt is a small municipality in the northeastern part of the German state of Baden-Württemberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Assamstadt Target entity description: Assamstadt is a small municipality in the northeastern part of the German state of Baden-Württemberg.
-
A.
Dibrugarh
Dibrugarh is a prominent city in northeastern India known as a major commercial and industrial hub of Assam, especially for its tea industry and oil and natural gas sectors.
-
B.
Chandanagar
Chandanagar is a residential and commercial suburb in the northwestern part of Hyderabad, India, known for its proximity to IT hubs and growing urban infrastructure.
-
C.
Agartala
Agartala is the capital city of the Indian state of Tripura and a major urban and economic center in Northeast India.
-
D.
Guwahati
Guwahati is a major city in northeastern India, serving as a key cultural, economic, and transportation hub for the region.
-
E.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa1aeac81909e8d97bd708c6b71 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012341b8e88190a2bee865be5ca1c1 |
completed | May 11, 2026, 12:30 a.m. |
| NEDg | Description generation | batch_6a012585a1548190a112f55e2d84ccac |
completed | May 11, 2026, 12:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0126536c348190b9b2eadb4969f8c2 |
completed | May 11, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:34 a.m.