Triple
T34594522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Docutils |
E888273
|
entity |
| Predicate | usesMarkupModel |
P74593
|
FINISHED |
| Object | document tree |
—
|
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: document tree | Statement: [Docutils, usesMarkupModel, document tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMarkupModel Context triple: [Docutils, usesMarkupModel, document tree]
-
A.
supportsMarkupStyle
chosen
Indicates that one entity is capable of handling, rendering, or otherwise working with a specified markup style associated with another entity.
-
B.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
C.
scopeModelUsed
Indicates that a particular model is employed or applied within a specified scope or context.
-
D.
usedMark
Indicates that one entity has employed or applied a particular mark, symbol, or indicator in some context or action.
-
E.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
- 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_69f349d3bfcc81909874c99e646fb3ea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 1, 2026, 2:03 a.m.