Triple
T34436989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ross Naess |
E883986
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object |
Leif Næss
Leif Næss is a member of the Næss family, known in part through his relationship as the sibling of Ross Naess, who is connected to the entertainment and music legacy of the Ross–Næss family.
|
E2097861
|
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: Leif Næss | Statement: [Ross Naess, sibling, Leif Næss]
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: Leif Næss Triple: [Ross Naess, sibling, Leif Næss]
Generated description
Leif Næss is a member of the Næss family, known in part through his relationship as the sibling of Ross Naess, who is connected to the entertainment and music legacy of the Ross–Næss family.
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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7191119b081909d5c230bc3d3e811 |
completed | May 3, 2026, 9:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a372127c2608190b9b23dae828a912b |
completed | June 20, 2026, 11:24 p.m. |
| NEDg | Description generation | batch_6a3721a992c08190a4579307d8174190 |
completed | June 20, 2026, 11:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a37221f4b9c8190964f222e14227227 |
completed | June 20, 2026, 11:28 p.m. |
Created at: May 1, 2026, 2 a.m.