Triple
T18613552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dankmar Adler |
E454959
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Stadtlengsfeld
Stadtlengsfeld is a small town in the Wartburg district of Thuringia, Germany, known historically as a rural community in central Germany.
|
E1334053
|
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: Stadtlengsfeld | Statement: [Dankmar Adler, placeOfBirth, Stadtlengsfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stadtlengsfeld Context triple: [Dankmar Adler, placeOfBirth, Stadtlengsfeld]
-
A.
Lengenfeld
Lengenfeld is a small town in the Free State of Saxony in eastern Germany, known as the birthplace of biblical scholar Constantin von Tischendorf.
-
B.
Kiefersfelden
Kiefersfelden is a Bavarian municipality near the Austrian border, known as a gateway to the Alps and a popular base for outdoor and cross-border travel.
-
C.
Ruhmannsfelden
Ruhmannsfelden is a small market town in the Bavarian Forest region of southeastern Germany.
-
D.
Burgfelden
Burgfelden is a village in the Swabian Jura region of Baden-Württemberg, Germany, now incorporated into the town of Albstadt.
-
E.
Eisfeld
Eisfeld is a small town in the Thuringia region of central Germany, known for its historical architecture and location along the Werra River.
- 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: Stadtlengsfeld Triple: [Dankmar Adler, placeOfBirth, Stadtlengsfeld]
Generated description
Stadtlengsfeld is a small town in the Wartburg district of Thuringia, Germany, known historically as a rural community in central Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stadtlengsfeld Target entity description: Stadtlengsfeld is a small town in the Wartburg district of Thuringia, Germany, known historically as a rural community in central Germany.
-
A.
Lengenfeld
Lengenfeld is a small town in the Free State of Saxony in eastern Germany, known as the birthplace of biblical scholar Constantin von Tischendorf.
-
B.
Kiefersfelden
Kiefersfelden is a Bavarian municipality near the Austrian border, known as a gateway to the Alps and a popular base for outdoor and cross-border travel.
-
C.
Ruhmannsfelden
Ruhmannsfelden is a small market town in the Bavarian Forest region of southeastern Germany.
-
D.
Burgfelden
Burgfelden is a village in the Swabian Jura region of Baden-Württemberg, Germany, now incorporated into the town of Albstadt.
-
E.
Eisfeld
Eisfeld is a small town in the Thuringia region of central Germany, known for its historical architecture and location along the Werra River.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54d030d488190a992d10d3d28b4ad |
completed | April 19, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05038c4d408190acb54ceaeaf470c5 |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a05065fcdd8819083644c9bceb556c9 |
completed | May 13, 2026, 11:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0506f2ff9c81909995a299641c6c37 |
completed | May 13, 2026, 11:19 p.m. |
Created at: April 10, 2026, 11:45 a.m.