Triple
T35606314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Wrath |
E1028903
|
entity |
| Predicate | hasNearbyFeature |
P350
|
FINISHED |
| Object |
Kearvaig Bothy
Kearvaig Bothy is a remote, free mountain shelter for walkers and cyclists on the wild northwestern coast of Scotland, popular with those exploring the Cape Wrath area.
|
E2147697
|
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: Kearvaig Bothy | Statement: [Cape Wrath, hasNearbyFeature, Kearvaig Bothy]
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: Kearvaig Bothy Triple: [Cape Wrath, hasNearbyFeature, Kearvaig Bothy]
Generated description
Kearvaig Bothy is a remote, free mountain shelter for walkers and cyclists on the wild northwestern coast of Scotland, popular with those exploring the Cape Wrath area.
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_69f76e0653ec81909b1b813c126c6574 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec6feb081909f570ed388565454 |
completed | May 3, 2026, 7:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a385be783a88190a5d15f3f6de0ca4d |
completed | June 21, 2026, 9:47 p.m. |
| NEDg | Description generation | batch_6a385cfee66c8190a546393089b8d789 |
completed | June 21, 2026, 9:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a385df5220881908ae1a6c6e999e3fa |
completed | June 21, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:05 p.m.