Triple
T27142201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knock Shrine |
E681843
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Knock, County Mayo
Knock, County Mayo is a village in western Ireland best known as a major Catholic pilgrimage site associated with the Knock Shrine and reported Marian apparition of 1879.
|
E1758709
|
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: Knock, County Mayo | Statement: [Knock Shrine, locatedIn, Knock, County Mayo]
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: Knock, County Mayo Triple: [Knock Shrine, locatedIn, Knock, County Mayo]
Generated description
Knock, County Mayo is a village in western Ireland best known as a major Catholic pilgrimage site associated with the Knock Shrine and reported Marian apparition of 1879.
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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f624c2ed0c819091dde69fc6084d4a |
completed | May 2, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12482558188190b768d43f0382d980 |
completed | May 24, 2026, 12:36 a.m. |
| NEDg | Description generation | batch_6a1249514a4881909357bb4e1c502d2b |
completed | May 24, 2026, 12:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a124a0a69188190a543bca2b05b2402 |
completed | May 24, 2026, 12:44 a.m. |
Created at: April 27, 2026, 9:10 a.m.