Triple
T23420878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic Diocese of Eger |
E560645
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Eger |
—
|
NE NERFINISHED |
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: Eger | Statement: [Roman Catholic Diocese of Eger, locatedIn, Eger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eger Context triple: [Roman Catholic Diocese of Eger, locatedIn, Eger]
-
A.
Eger
chosen
Eger is a historic city in northern Hungary known for its baroque architecture, castle, and wine culture.
-
B.
Eger
Eger is the former German name for the Czech town of Cheb, a historic settlement near the German border in western Bohemia.
-
C.
EGER
EGER is the ICAO airport code for Stronsay Airport, a small regional airfield serving the island of Stronsay in Orkney, Scotland.
-
D.
Egerszalók
Egerszalók is a Hungarian village famous for its thermal springs and striking terraced salt hill spa complex.
-
E.
Gyor
Győr is a historic city in northwestern Hungary, strategically located at the confluence of the Danube, Rába, and Rábca rivers and known as an important regional industrial and cultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a54605dc81909aad9834ef6ff8a1 |
completed | April 29, 2026, 6:29 a.m. |
Created at: April 17, 2026, 5:45 p.m.