Triple
T30917939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsch Eylau |
E787633
|
entity |
| Predicate | wasPartOf |
P35
|
FINISHED |
| Object |
Kreis Deutsch Eylau
Kreis Deutsch Eylau was a former administrative district in West Prussia within the Kingdom of Prussia and later Germany, centered around the town of Deutsch Eylau (now Iława, Poland).
|
E1938370
|
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: Kreis Deutsch Eylau | Statement: [Deutsch Eylau, wasPartOf, Kreis Deutsch Eylau]
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: Kreis Deutsch Eylau Triple: [Deutsch Eylau, wasPartOf, Kreis Deutsch Eylau]
Generated description
Kreis Deutsch Eylau was a former administrative district in West Prussia within the Kingdom of Prussia and later Germany, centered around the town of Deutsch Eylau (now Iława, Poland).
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_69f224bfaca88190b9d0dfcc86297fe9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f692b307488190a155de7798ec22fe |
completed | May 3, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a28e467d0448190ade59fb9b002d5b5 |
completed | June 10, 2026, 4:13 a.m. |
| NEDg | Description generation | batch_6a28e6df61d0819097dad3b8fe0605dc |
completed | June 10, 2026, 4:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28e77c979c8190ad64292260d34595 |
completed | June 10, 2026, 4:26 a.m. |
Created at: April 29, 2026, 8:51 p.m.