Triple
T10333619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harz district |
E242940
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ilsenburg
Ilsenburg is a small town in the northern Harz region of Saxony-Anhalt, Germany, known for its scenic location near the Harz mountains and its historic monastery.
|
E878542
|
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: Ilsenburg | Statement: [Harz district, contains, Ilsenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ilsenburg Context triple: [Harz district, contains, Ilsenburg]
-
A.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
B.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Stühlingen
Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
-
D.
Treuchtlingen
Treuchtlingen is a small town in the Bavarian region of Germany, known for its location in the Altmühl Valley and its role as a local railway junction and spa destination.
-
E.
Irschenhausen
Irschenhausen is a small village in Bavaria, Germany, known in part as the place where German field marshal Erich von Manstein died.
- 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: Ilsenburg Triple: [Harz district, contains, Ilsenburg]
Generated description
Ilsenburg is a small town in the northern Harz region of Saxony-Anhalt, Germany, known for its scenic location near the Harz mountains and its historic monastery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ilsenburg Target entity description: Ilsenburg is a small town in the northern Harz region of Saxony-Anhalt, Germany, known for its scenic location near the Harz mountains and its historic monastery.
-
A.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
B.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Stühlingen
Stühlingen is a small town in the state of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its scenic setting in the Black Forest region.
-
D.
Treuchtlingen
Treuchtlingen is a small town in the Bavarian region of Germany, known for its location in the Altmühl Valley and its role as a local railway junction and spa destination.
-
E.
Irschenhausen
Irschenhausen is a small village in Bavaria, Germany, known in part as the place where German field marshal Erich von Manstein died.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4dfc366b481909c49f199892e9d42 |
completed | April 7, 2026, 10:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98811fd3881909369e0f00f2a8267 |
completed | April 10, 2026, 11:30 p.m. |
| NEDg | Description generation | batch_69d98bf7a070819097b41b5018ef21f9 |
completed | April 10, 2026, 11:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98c5d0d088190bbcf08b3b5b14b49 |
completed | April 10, 2026, 11:48 p.m. |
Created at: April 6, 2026, 11:53 a.m.