Triple
T18266269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | noweb |
E437491
|
entity |
| Predicate | markup |
P130
|
FINISHED |
| Object | uses double angle brackets for code chunks |
—
|
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: uses double angle brackets for code chunks | Statement: [noweb, markup, uses double angle brackets for code chunks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: markup Context triple: [noweb, markup, uses double angle brackets for code chunks]
-
A.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
B.
marked
Indicates that one entity has been identified, labeled, or highlighted in some way by another entity.
-
C.
margining
Indicates the process of posting, adjusting, or settling collateral (margin) between parties to secure obligations in a financial transaction or trading relationship.
-
D.
format
chosen
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
E.
marque
Indicates that one entity is the brand or make associated with another entity, such as a product, vehicle, or manufactured item.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7af85c81909859e7247738a535 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.