Triple
T22000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autobiography of Andrew Carnegie |
E437
|
entity |
| Predicate | portrays |
P264
|
FINISHED |
| Object | Carnegie as a self-made man |
—
|
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: Carnegie as a self-made man | Statement: [Autobiography of Andrew Carnegie, portrays, Carnegie as a self-made man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrays Context triple: [Autobiography of Andrew Carnegie, portrays, Carnegie as a self-made man]
-
A.
describes
chosen
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
B.
presentedBy
Indicates that something (such as an event, performance, or work) is formally organized, hosted, or introduced by a particular person or entity.
-
C.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
promotes
Indicates that one entity actively supports, advances, or encourages the growth, adoption, or success of another entity or outcome.
-
E.
produces
Indicates that one entity creates, generates, or yields another entity as a result or output.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24654724481909ba14b7f68d2a472 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.