Triple
T12638799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeim district |
E301836
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Hardegsen
Hardegsen is a small town in Lower Saxony, Germany, known for its medieval castle and historic town center.
|
E1009019
|
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: Hardegsen | Statement: [Northeim district, containsMunicipality, Hardegsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hardegsen Context triple: [Northeim district, containsMunicipality, Hardegsen]
-
A.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
B.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
C.
Haderup
Haderup is a small town in Denmark, known locally as a rural community that gave its name to the former Aulum-Haderup Municipality.
-
D.
Hollenstedt
Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
-
E.
Zahle
Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
- 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: Hardegsen Triple: [Northeim district, containsMunicipality, Hardegsen]
Generated description
Hardegsen is a small town in Lower Saxony, Germany, known for its medieval castle and historic town center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hardegsen Target entity description: Hardegsen is a small town in Lower Saxony, Germany, known for its medieval castle and historic town center.
-
A.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
B.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
C.
Haderup
Haderup is a small town in Denmark, known locally as a rural community that gave its name to the former Aulum-Haderup Municipality.
-
D.
Hollenstedt
Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
-
E.
Zahle
Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961499de08190bdba66ca40b021be |
completed | April 10, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a539f098819096e955a035742dad |
completed | May 3, 2026, 1:30 a.m. |
| NEDg | Description generation | batch_69f6a724e414819081c95b0d4ac0da25 |
completed | May 3, 2026, 1:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6a7def4bc8190836ad781a4a28456 |
completed | May 3, 2026, 1:41 a.m. |
Created at: April 9, 2026, 5:16 p.m.