Triple
T199905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Nelson (publisher family) |
E4079
|
entity |
| Predicate | continuedInfluenceInto |
P9
|
FINISHED |
| Object | 20th century |
—
|
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: 20th century | Statement: [Thomas Nelson (publisher family), continuedInfluenceInto, 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: continuedInfluenceInto Context triple: [Thomas Nelson (publisher family), continuedInfluenceInto, 20th century]
-
A.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
B.
influencedWork
Indicates that one work has had a significant impact on the creation, style, content, or development of another work.
-
C.
partOfContinuum
Indicates that one entity exists as a segment or phase within a continuous sequence, range, or progression that includes the other entity.
-
D.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
E.
hasHistoricalWritingInfluenceFrom
Indicates that one entity’s historical writing style, content, or traditions are influenced by those of 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.