Triple
T29183350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Animal Farm |
E739800
|
entity |
| Predicate | notableCommandment |
P60020
|
FINISHED |
| Object | All animals are equal |
—
|
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: All animals are equal | Statement: [Animal Farm, notableCommandment, All animals are equal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCommandment Context triple: [Animal Farm, notableCommandment, All animals are equal]
-
A.
containsCommandment
chosen
Indicates that one entity includes or encompasses a specific commandment as part of its content or structure.
-
B.
receivedCommandment
Indicates that one entity has been given or entrusted with a commandment, directive, or moral instruction from another entity.
-
C.
commandmentType
Indicates the specific category or kind of commandment that an instruction or directive belongs to.
-
D.
discussesCommandment
Indicates that one entity engages in discussion or discourse about a particular commandment associated with another entity.
-
E.
numberOfCommandments
Indicates the total count of commandments associated with a given subject.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a030e31e01881909c6032532cd3c31a |
completed | May 12, 2026, 11:25 a.m. |
| PD | Predicate disambiguation | batch_6a030dadea008190abe0a5652784bdd6 |
completed | May 12, 2026, 11:23 a.m. |
Created at: April 28, 2026, 11:58 a.m.