Triple
T1188188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nielsen |
E25294
|
entity |
| Predicate | suffixMeaning |
P16024
|
FINISHED |
| Object | -sen means son of in Danish |
—
|
LITERAL 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: -sen means son of in Danish | Statement: [Nielsen, suffixMeaning, -sen means son of in Danish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suffixMeaning Context triple: [Nielsen, suffixMeaning, -sen means son of in Danish]
-
A.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
B.
meaningComponent
chosen
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
C.
meaningOfPhrase
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
D.
etymologicalRootMeaning
Indicates that one term’s meaning originates from or is derived from the historical or original meaning of another term.
-
E.
secondDefinition
Indicates that one entity serves as an alternative or secondary definition or meaning for another entity.
- F. None of above.
Provenance (3 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd568cf481908d10cf19a3ce28f3 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.