Triple
T501892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fascist Italy |
E10418
|
entity |
| Predicate | introducedLaw |
P513
|
FINISHED |
| Object | racial laws of 1938 |
—
|
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: racial laws of 1938 | Statement: [Fascist Italy, introducedLaw, racial laws of 1938]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedLaw Context triple: [Fascist Italy, introducedLaw, racial laws of 1938]
-
A.
passedLegislation
Indicates that a governing body has formally approved and enacted a specific piece of legislation or law.
-
B.
introduced
chosen
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
C.
relatedLegislation
Indicates that there exists a legislative document that is connected to, affects, or is otherwise relevant to the subject entity.
-
D.
numberOfLaws
Indicates the quantitative count of laws associated with a given entity or context.
-
E.
typeOfLegislation
Indicates the specific category or kind of legislation that a given legal act or measure belongs to.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1339748819089f89691a1698dd9 |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfbb7e0819092cf29c2c68fe8fb |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.