Triple
T4142893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Sprat |
E89310
|
entity |
| Predicate | lexicalCategory |
P12863
|
FINISHED |
| Object | proper noun |
—
|
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: proper noun | Statement: [Jack Sprat, lexicalCategory, proper noun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lexicalCategory Context triple: [Jack Sprat, lexicalCategory, proper noun]
-
A.
lexicalItem
Indicates that one entity is a word or vocabulary unit associated with, or used to express, another entity (such as a concept, meaning, or linguistic entry).
-
B.
grammaticalType
chosen
Indicates the grammatical category or role (such as part of speech or syntactic function) that an expression has within a language.
-
C.
classificationTerm
Indicates that one entity serves as a categorical label or type used to classify or group another entity.
-
D.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
E.
linguisticClassification
Indicates the relationship by which an entity is categorized according to its language or linguistic type.
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.