Triple
T14478902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Rule of Evidence 1003 |
E359048
|
entity |
| Predicate | languageCore |
P114350
|
FINISHED |
| Object | A duplicate is admissible to the same extent as the original |
—
|
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: A duplicate is admissible to the same extent as the original | Statement: [Federal Rule of Evidence 1003, languageCore, A duplicate is admissible to the same extent as the original]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCore Context triple: [Federal Rule of Evidence 1003, languageCore, A duplicate is admissible to the same extent as the original]
-
A.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
B.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924a576c819098351efabdb779b1 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:20 a.m.