Triple
T3746836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hensoldt |
E81229
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object |
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
|
E407068
|
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: Taufkirchen | Statement: [Hensoldt, headquartersLocation, Taufkirchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taufkirchen Context triple: [Hensoldt, headquartersLocation, Taufkirchen]
-
A.
Altötting
Altötting is a Bavarian pilgrimage town renowned as one of Germany’s most important Catholic shrines, centered around the Chapel of Grace and its venerated Black Madonna.
-
B.
Pfarrkirchen
Pfarrkirchen is a small Bavarian town in southeastern Germany known as the administrative center of the Rottal-Inn district.
-
C.
Weilheim an der Teck
Weilheim an der Teck is a small historic town in the German state of Baden-Württemberg, located at the foot of the Swabian Alps in southern Germany.
-
D.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
E.
Lauingen
Lauingen is a historic Bavarian town in southern Germany, best known as the birthplace of the medieval scholar and philosopher Albert the Great.
- 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: Taufkirchen Triple: [Hensoldt, headquartersLocation, Taufkirchen]
Generated description
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taufkirchen Target entity description: Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
A.
Altötting
Altötting is a Bavarian pilgrimage town renowned as one of Germany’s most important Catholic shrines, centered around the Chapel of Grace and its venerated Black Madonna.
-
B.
Pfarrkirchen
Pfarrkirchen is a small Bavarian town in southeastern Germany known as the administrative center of the Rottal-Inn district.
-
C.
Weilheim an der Teck
Weilheim an der Teck is a small historic town in the German state of Baden-Württemberg, located at the foot of the Swabian Alps in southern Germany.
-
D.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
E.
Lauingen
Lauingen is a historic Bavarian town in southern Germany, best known as the birthplace of the medieval scholar and philosopher Albert the Great.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb69887c8190a3f1188ec85727b0 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c2971788190b8f48da3883d2ba2 |
completed | March 14, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69b55004ef54819090a714478a8ff6e8 |
completed | March 14, 2026, 12:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5508ab77c819080cd8a87818ea482 |
completed | March 14, 2026, 12:11 p.m. |
Created at: March 8, 2026, 3:35 p.m.