Triple
T11885459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladek Spiegelman |
E282768
|
entity |
| Predicate | placeOfResidence |
P75
|
FINISHED |
| Object | Czestochowa |
E128038
|
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: Czestochowa | Statement: [Vladek Spiegelman, placeOfResidence, Czestochowa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Czestochowa Context triple: [Vladek Spiegelman, placeOfResidence, Czestochowa]
-
A.
Częstochowa
chosen
Częstochowa is a city in southern Poland best known as a major Catholic pilgrimage center, home to the Jasna Góra Monastery and the revered Black Madonna icon.
-
B.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
-
C.
Katowice
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
-
D.
Wrocław
Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
-
E.
Kielce
Kielce is a city in south-central Poland known as an important regional center for industry, education, and culture.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a13370819086386fecb99e4f0b |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd9495b9748190905b02621939b326 |
completed | May 8, 2026, 7:45 a.m. |
Created at: April 8, 2026, 9:44 p.m.