Triple
T8338354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Styria |
E195845
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Voitsberg
Voitsberg is a small town in southeastern Austria known for its industrial heritage and location within the federal state of Styria.
|
E730298
|
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: Voitsberg | Statement: [Styria, hasCity, Voitsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Voitsberg Context triple: [Styria, hasCity, Voitsberg]
-
A.
Weisselberg
Weisselberg is a surname most prominently associated with Allen Weisselberg, the longtime chief financial officer of the Trump Organization.
-
B.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
-
C.
Kleeberg
Kleeberg is a Polish surname most notably associated with General Franciszek Kleeberg, a commander in the early stages of World War II.
-
D.
Gaisbach
Gaisbach is a village and district of the town of Oberkirch in the state of Baden-Württemberg in southwestern Germany.
-
E.
Vogelthal
Vogelthal is a small village in Bavaria, Germany, known as the birthplace of World War II tank commander Michael Wittmann.
- 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: Voitsberg Triple: [Styria, hasCity, Voitsberg]
Generated description
Voitsberg is a small town in southeastern Austria known for its industrial heritage and location within the federal state of Styria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Voitsberg Target entity description: Voitsberg is a small town in southeastern Austria known for its industrial heritage and location within the federal state of Styria.
-
A.
Weisselberg
Weisselberg is a surname most prominently associated with Allen Weisselberg, the longtime chief financial officer of the Trump Organization.
-
B.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
-
C.
Kleeberg
Kleeberg is a Polish surname most notably associated with General Franciszek Kleeberg, a commander in the early stages of World War II.
-
D.
Gaisbach
Gaisbach is a village and district of the town of Oberkirch in the state of Baden-Württemberg in southwestern Germany.
-
E.
Vogelthal
Vogelthal is a small village in Bavaria, Germany, known as the birthplace of World War II tank commander Michael Wittmann.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd68e348190a7cb8639a263b50f |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde794a4008190bbcb2f114c503458 |
completed | April 2, 2026, 3:50 a.m. |
| NEDg | Description generation | batch_69cdebf81adc81908feb7b19b5b151c3 |
completed | April 2, 2026, 4:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdecc83e408190b9ba1dc8acf5081b |
completed | April 2, 2026, 4:12 a.m. |
Created at: March 30, 2026, 5:57 p.m.