Triple
T4428966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grizzlys Wolfsburg |
E95276
|
entity |
| Predicate | represents |
P129
|
FINISHED |
| Object | city of Wolfsburg |
E74139
|
NE FINISHED |
How this triple was built (2 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: city of Wolfsburg | Statement: [Grizzlys Wolfsburg, represents, city of Wolfsburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Wolfsburg Context triple: [Grizzlys Wolfsburg, represents, city of Wolfsburg]
-
A.
Wolfsburg
chosen
Wolfsburg is a German city best known as the headquarters and main production site of the Volkswagen automobile company.
-
B.
Ingolstadt
Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
-
C.
Volkswagen Autostadt
Volkswagen Autostadt is an automotive-themed visitor attraction and museum complex in Wolfsburg, Germany, showcasing Volkswagen Group brands, car production, and modern architecture.
-
D.
Gauting
Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
-
E.
Stadt Nürnberg
Stadt Nürnberg is the municipal government of the German city of Nuremberg, responsible for local administration, public services, and urban infrastructure.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35568767c819084d5e18b56a4745e |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6136caa248190a84423cede1908c3 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:30 p.m.