Triple
T34954633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | l3kernel |
E1008093
|
entity |
| Predicate | scopeModel |
P127170
|
FINISHED |
| Object | TeX group-based scoping |
—
|
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: TeX group-based scoping | Statement: [l3kernel, scopeModel, TeX group-based scoping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scopeModel Context triple: [l3kernel, scopeModel, TeX group-based scoping]
-
A.
scopeModelUsed
chosen
Indicates that a particular model is employed or applied within a specified scope or context.
-
B.
scopeValue
Indicates that one entity specifies or constrains the quantitative or qualitative extent (scope) applicable to another entity or context.
-
C.
scopeType
Indicates the specific range, level, or context within which a given relationship, rule, or action is defined or applies.
-
D.
focusModel
Indicates that one entity serves as the primary or central model that another entity is directed toward, based on, or concentrated on.
-
E.
namespaceModel
Indicates a relationship where a model is defined within, or associated with, a particular namespace or logical grouping.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.