Triple
T32785854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stroma |
E838494
|
entity |
| Predicate | nearbyTidalRace |
P65074
|
FINISHED |
| Object |
Merry Men of Mey
The Merry Men of Mey are a notorious tidal race off the north coast of Scotland, known for their powerful, turbulent waters and hazardous conditions for navigation.
|
E2022528
|
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: Merry Men of Mey | Statement: [Stroma, nearbyTidalRace, Merry Men of Mey]
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: Merry Men of Mey Triple: [Stroma, nearbyTidalRace, Merry Men of Mey]
Generated description
The Merry Men of Mey are a notorious tidal race off the north coast of Scotland, known for their powerful, turbulent waters and hazardous conditions for navigation.
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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fdda07679481908536fab0cc8c603e |
completed | May 8, 2026, 12:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34b1666e34819094889e084aa6d951 |
completed | June 19, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_6a34b226f710819086b2d0bee27a8c79 |
completed | June 19, 2026, 3:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a34b2b0f36c8190ab30af3d30024b97 |
completed | June 19, 2026, 3:08 a.m. |
Created at: May 1, 2026, 1:14 a.m.