Triple
T34227656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serra del Cadí |
E878097
|
entity |
| Predicate | hasPass |
P11208
|
FINISHED |
| Object |
Coll de Pal
Coll de Pal is a high mountain pass in the Catalan Pyrenees, known for connecting valleys in the Serra del Cadí and serving as a scenic route for hikers and cyclists.
|
E2088105
|
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: Coll de Pal | Statement: [Serra del Cadí, hasPass, Coll de Pal]
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: Coll de Pal Triple: [Serra del Cadí, hasPass, Coll de Pal]
Generated description
Coll de Pal is a high mountain pass in the Catalan Pyrenees, known for connecting valleys in the Serra del Cadí and serving as a scenic route for hikers and cyclists.
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_69f349b16d0481908754e3069f05e0c1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f710ae052c8190bc5a79584d292c1c |
completed | May 3, 2026, 9:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36d5e0e84c8190a0a23bc12a3548eb |
completed | June 20, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_6a36d655b27481908d135622a2e913bd |
completed | June 20, 2026, 6:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a36d81de0dc81908acd6add10d2f5cd |
completed | June 20, 2026, 6:12 p.m. |
Created at: May 1, 2026, 1:56 a.m.