Triple
T16901582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inowrazław |
E424449
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Inowroclaw
Inowroclaw is a historic spa and industrial city in north-central Poland, known for its saltworks and therapeutic brine baths.
|
E1582921
|
NE FINISHED |
How this triple was built (4 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: Inowroclaw | Statement: [Inowrazław, hasAlternativeName, Inowroclaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inowroclaw Context triple: [Inowrazław, hasAlternativeName, Inowroclaw]
-
A.
Lublin
Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
-
B.
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.
-
C.
Łódź
Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
-
D.
Wolsztyn
Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
-
E.
Lubawa
Lubawa is a historic town in northern Poland known for its medieval heritage and location within the Warmian-Masurian region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Inowroclaw Triple: [Inowrazław, hasAlternativeName, Inowroclaw]
Generated description
Inowroclaw is a historic spa and industrial city in north-central Poland, known for its saltworks and therapeutic brine baths.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Inowroclaw Target entity description: Inowroclaw is a historic spa and industrial city in north-central Poland, known for its saltworks and therapeutic brine baths.
-
A.
Lublin
Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
-
B.
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.
-
C.
Łódź
Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
-
D.
Wolsztyn
Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
-
E.
Lubawa
Lubawa is a historic town in northern Poland known for its medieval heritage and location within the Warmian-Masurian region.
- F. None of above. chosen
Provenance (5 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8dc7cf08190ad935935d8daf1d0 |
completed | April 18, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5da47b648190a4ba7792f2b36999 |
completed | May 19, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_6a0c60283668819096076b1bf406eaa0 |
completed | May 19, 2026, 1:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c60b52fe88190854803902df750c5 |
completed | May 19, 2026, 1:08 p.m. |
Created at: April 10, 2026, 5:29 a.m.