Triple
T289330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | On the Origin of Species |
E5954
|
entity |
| Predicate | religiousReception |
P9411
|
FINISHED |
| Object | mixed |
—
|
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: mixed | Statement: [On the Origin of Species, religiousReception, mixed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousReception Context triple: [On the Origin of Species, religiousReception, mixed]
-
A.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
B.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
C.
religiousTrend
Indicates a pattern or direction of change over time in religious beliefs, practices, or affiliations among entities.
-
D.
religiousFunction
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
-
E.
recognizesReligion
Indicates that one entity formally acknowledges or accepts another entity as a valid or legitimate religion.
- F. None of above. chosen
Provenance (4 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e4df5508190ab75115ac6b3964e |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7d089081909810442c3d0182f6 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d0ec71081908478c800be4f7bb0 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.