Triple
T11691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gospel of Wealth |
E238
|
entity |
| Predicate | relatedWork |
P37
|
FINISHED |
| Object | Andrew Carnegie’s philanthropic endowments |
—
|
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: Andrew Carnegie’s philanthropic endowments | Statement: [The Gospel of Wealth, relatedWork, Andrew Carnegie’s philanthropic endowments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedWork Context triple: [The Gospel of Wealth, relatedWork, Andrew Carnegie’s philanthropic endowments]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
C.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
D.
notableWork
Indicates that one entity is a significant or well-known work (such as a book, artwork, or creation) produced by another entity.
-
E.
relatedAward
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fe7da8c8190aea795b62cb91621 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.