Triple
T23177214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idings |
E579036
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object |
Eadberht of Northumbria
Eadberht of Northumbria was an 8th-century king of the Anglo-Saxon kingdom of Northumbria, noted for his military campaigns and efforts to consolidate royal authority.
|
E1719965
|
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: Eadberht of Northumbria | Statement: [Idings, hasNotableMember, Eadberht of Northumbria]
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: Eadberht of Northumbria Triple: [Idings, hasNotableMember, Eadberht of Northumbria]
Generated description
Eadberht of Northumbria was an 8th-century king of the Anglo-Saxon kingdom of Northumbria, noted for his military campaigns and efforts to consolidate royal authority.
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_69e245fd2a388190b814c0dfa15f7148 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f6b823c8190a2d39c54e48a1001 |
completed | April 29, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a119a1126648190b02638a1ac43216a |
completed | May 23, 2026, 12:14 p.m. |
| NEDg | Description generation | batch_6a119ad502f4819094bacc5b50514200 |
completed | May 23, 2026, 12:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a119b5af6f48190a607628edf5bd0c8 |
completed | May 23, 2026, 12:19 p.m. |
Created at: April 17, 2026, 4:04 p.m.