Triple
T8338352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Styria |
E195845
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Weiz
Weiz is a small industrial and cultural town in the Austrian state of Styria, known for its engineering companies and picturesque setting near the Alps.
|
E728310
|
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: Weiz | Statement: [Styria, hasCity, Weiz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weiz Context triple: [Styria, hasCity, Weiz]
-
A.
Beran
Beran is a Czech surname most notably borne by Rudolf Beran, a prominent Czechoslovak politician and prime minister before and during the early years of World War II.
-
B.
Weidling
Weidling is a German surname most notably associated with General Helmuth Weidling, the last commander of Berlin’s defenses in World War II.
-
C.
Bavier
Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
-
D.
Fürth
Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
-
E.
Essling
Essling is a village near Vienna, Austria, historically notable as one of the sites of the 1809 Battle of Aspern-Essling during the Napoleonic Wars.
- 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: Weiz Triple: [Styria, hasCity, Weiz]
Generated description
Weiz is a small industrial and cultural town in the Austrian state of Styria, known for its engineering companies and picturesque setting near the Alps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weiz Target entity description: Weiz is a small industrial and cultural town in the Austrian state of Styria, known for its engineering companies and picturesque setting near the Alps.
-
A.
Beran
Beran is a Czech surname most notably borne by Rudolf Beran, a prominent Czechoslovak politician and prime minister before and during the early years of World War II.
-
B.
Weidling
Weidling is a German surname most notably associated with General Helmuth Weidling, the last commander of Berlin’s defenses in World War II.
-
C.
Bavier
Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
-
D.
Fürth
Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
-
E.
Essling
Essling is a village near Vienna, Austria, historically notable as one of the sites of the 1809 Battle of Aspern-Essling during the Napoleonic Wars.
- 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_69cdc71a9abc8190881ff73c6fe851cd |
completed | April 2, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69cdcb90bec88190a2c19681405aa13e |
completed | April 2, 2026, 1:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdcd0fc9488190a0a576c385b9bc1f |
completed | April 2, 2026, 1:57 a.m. |
Created at: March 30, 2026, 5:57 p.m.