Triple
T12888420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince-Bishopric of Verden |
E308291
|
entity |
| Predicate | hasCapitalCity |
P204
|
FINISHED |
| Object | Verden |
E177243
|
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: Verden | Statement: [Prince-Bishopric of Verden, hasCapitalCity, Verden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verden Context triple: [Prince-Bishopric of Verden, hasCapitalCity, Verden]
-
A.
Verden
chosen
Verden is a historic town in Lower Saxony, Germany, known for its medieval cathedral and location along the Weser River.
-
B.
Erda
Erda is the earth goddess and prophetic figure in Richard Wagner’s Ring Cycle, renowned for her wisdom and warnings to the gods.
-
C.
Świecie
Świecie is a historic town in northern Poland, located in the Kuyavian-Pomeranian Voivodeship and known for its medieval castle and position near the confluence of the Vistula and Wda rivers.
-
D.
Erdek
Erdek is a coastal town and popular seaside resort in Turkey’s Balıkesir Province, located on the Kapıdağ Peninsula along the Sea of Marmara.
-
E.
Terra
Terra is a character from the film "I, Frankenstein," depicted as a central figure within its dark, supernatural world of gargoyles and demons.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714581988190afc720ffd7797860 |
completed | April 10, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a5576ae4819084914697b2e86d9f |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:39 p.m.