Triple
T24361635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Val di Fiemme |
E614075
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ziano di Fiemme
Ziano di Fiemme is a small alpine village and municipality in the Trentino region of northern Italy, known for its scenic setting in the Dolomites and its role as a mountain tourism and winter sports destination.
|
E1635810
|
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: Ziano di Fiemme | Statement: [Val di Fiemme, contains, Ziano di Fiemme]
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: Ziano di Fiemme Triple: [Val di Fiemme, contains, Ziano di Fiemme]
Generated description
Ziano di Fiemme is a small alpine village and municipality in the Trentino region of northern Italy, known for its scenic setting in the Dolomites and its role as a mountain tourism and winter sports destination.
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_69e2d7dfe7f08190b7a1f3a36483ab05 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29384a2f88190885eb141c5c44a2d |
completed | April 29, 2026, 11:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fe3553454819085c5a4e7321e5052 |
completed | May 22, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_6a0fe5e17f2081908024605c26ed76ae |
completed | May 22, 2026, 5:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0fe6407d3c819093016bab9d877286 |
completed | May 22, 2026, 5:14 a.m. |
Created at: April 18, 2026, 2 a.m.