Triple
T31262811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ofen Pass |
E797168
|
entity |
| Predicate | hasNameInItalian |
P17612
|
FINISHED |
| Object |
Passo del Forno
Passo del Forno is the Italian name for the Ofen Pass, a high mountain pass in the Swiss Alps connecting the Engadine valley with the Val Müstair.
|
E1954108
|
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: Passo del Forno | Statement: [Ofen Pass, hasNameInItalian, Passo del Forno]
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: Passo del Forno Triple: [Ofen Pass, hasNameInItalian, Passo del Forno]
Generated description
Passo del Forno is the Italian name for the Ofen Pass, a high mountain pass in the Swiss Alps connecting the Engadine valley with the Val Müstair.
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_69f224dd5fdc81908a4cd24917b67668 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69d8de8448190b337feaed4883acc |
completed | May 3, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a296bfc462c8190a62caec416fb8fb3 |
completed | June 10, 2026, 1:51 p.m. |
| NEDg | Description generation | batch_6a296fe7a5848190bb96205a6ede9dc2 |
completed | June 10, 2026, 2:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a29a7f163ac819080e504a3bd158340 |
completed | June 10, 2026, 6:07 p.m. |
Created at: April 29, 2026, 9:12 p.m.