Triple
T24799265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Île d’Ouessant |
E620473
|
entity |
| Predicate | fauna |
P950
|
FINISHED |
| Object |
Ouessant sheep
The Ouessant sheep is a very small, hardy heritage breed of domestic sheep from the island of Ouessant off the coast of Brittany, known for its fine wool and ability to thrive in harsh maritime climates.
|
E1654636
|
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: Ouessant sheep | Statement: [Île d’Ouessant, fauna, Ouessant sheep]
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: Ouessant sheep Triple: [Île d’Ouessant, fauna, Ouessant sheep]
Generated description
The Ouessant sheep is a very small, hardy heritage breed of domestic sheep from the island of Ouessant off the coast of Brittany, known for its fine wool and ability to thrive in harsh maritime climates.
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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f412a8d7d081909a4b961eadefd30e |
completed | May 1, 2026, 2:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a101c3148b881909b3ebcd03675cb74 |
completed | May 22, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_6a1028143b4c8190b89ad73aecb56e0d |
completed | May 22, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1029a084708190a87c7d2add8f4688 |
completed | May 22, 2026, 10:02 a.m. |
Created at: April 18, 2026, 4:49 a.m.