Triple
T5368618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum Island |
E108790
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Mitte |
E28609
|
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: Mitte | Statement: [Museum Island, locatedIn, Mitte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mitte Context triple: [Museum Island, locatedIn, Mitte]
-
A.
Mitte
chosen
Mitte is the central district of Berlin, Germany, known as the historic core of the city and home to many major landmarks and government institutions.
-
B.
Middleside
Middleside is a district or area within Fort Mills, historically associated with the British military presence on Hong Kong’s Stonecutters Island.
-
C.
Middelaar
Middelaar is a village in the Dutch province of Limburg, situated near the river Maas and close to the border with Germany.
-
D.
Centre
Centre was the former name of the administrative region in central France now known as Centre-Val de Loire.
-
E.
Midgley
Midgley is a small village in West Yorkshire, England, known for its rural setting in the Calder Valley near Luddenden Foot.
- 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_69bd440c77948190aad2a5f39b7b80f5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd86856f688190a34ab93619bae134 |
completed | March 20, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf292c4d1c819088f7b977ac212688 |
completed | March 21, 2026, 11:26 p.m. |
Created at: March 20, 2026, 2:02 p.m.