Triple
T9064774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adolf Loos |
E217217
|
entity |
| Predicate | educatedAt |
P5
|
FINISHED |
| Object | Realschule in Liberec |
E188165
|
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: Realschule in Liberec | Statement: [Adolf Loos, educatedAt, Realschule in Liberec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Realschule in Liberec Context triple: [Adolf Loos, educatedAt, Realschule in Liberec]
-
A.
Libeň
Libeň is a district in Prague known for its mix of residential areas, industrial heritage, and major venues such as the O2 Arena.
-
B.
Slavkov u Brna
Slavkov u Brna is a historic Czech town best known as the site of the Battle of Austerlitz, one of Napoleon’s most famous victories.
-
C.
Liberec
chosen
Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
-
D.
Havířov
Havířov is an industrial city in the Moravian-Silesian Region of the Czech Republic, known as one of the country’s youngest cities and a post-war planned urban center.
-
E.
Nymburk
Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc94bb26588190b7d6f2d70819e86f |
completed | April 1, 2026, 3:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d017a3926881909140f59c60ec3588 |
completed | April 3, 2026, 7:40 p.m. |
Created at: March 30, 2026, 7:11 p.m.