Triple
T3508539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolfsburg |
E74139
|
entity |
| Predicate | locatedBetween |
P1262
|
FINISHED |
| Object | Hannover |
E21642
|
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: Hannover | Statement: [Wolfsburg, locatedBetween, Hannover]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannover Context triple: [Wolfsburg, locatedBetween, Hannover]
-
A.
Bremen
Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
-
B.
Braunschweig
Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
-
C.
Hanover
Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
-
D.
Hanover
Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
-
E.
Hanover
chosen
Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc0cc394819087a9b598023f4f93 |
completed | March 8, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f59074e881908d346937da0b056e |
completed | March 14, 2026, 11:56 p.m. |
Created at: March 8, 2026, 3:18 p.m.