Triple
T32312724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brenner Pass |
E825543
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Gries am Brenner
Gries am Brenner is a small Austrian municipality in Tyrol, known as a traditional transit and alpine village just north of the Italian border in the Eastern Alps.
|
E2001820
|
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: Gries am Brenner | Statement: [Brenner Pass, locatedNear, Gries am Brenner]
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: Gries am Brenner Triple: [Brenner Pass, locatedNear, Gries am Brenner]
Generated description
Gries am Brenner is a small Austrian municipality in Tyrol, known as a traditional transit and alpine village just north of the Italian border in the Eastern Alps.
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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bdb8755481908645da7ceef44e17 |
completed | May 3, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a305717c4dc8190ab084323dc9469a8 |
completed | June 15, 2026, 7:48 p.m. |
| NEDg | Description generation | batch_6a305b4b640c8190a8e9166c63a9de7b |
completed | June 15, 2026, 8:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a305bda28e88190b451fd544cc157fb |
completed | June 15, 2026, 8:08 p.m. |
Created at: May 1, 2026, 12:46 a.m.