Triple
T26376213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herb Sutter |
E660907
|
entity |
| Predicate | topicOfWriting |
P97423
|
FINISHED |
| Object | C++ language evolution |
—
|
NE NERFINISHED |
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: C++ language evolution | Statement: [Herb Sutter, topicOfWriting, C++ language evolution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicOfWriting Context triple: [Herb Sutter, topicOfWriting, C++ language evolution]
-
A.
topicOfDialogue
Indicates that a particular subject or theme is the main focus of a dialogue or conversation between entities.
-
B.
writingFocus
Indicates that an entity’s primary attention or effort is directed toward writing or written expression.
-
C.
fieldOfWriting
chosen
Indicates that one entity is the domain, genre, or subject area in which another entity writes or produces written work.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
bestWritingCategoryName
Indicates the specific writing category that is considered the best or most appropriate for an entity.
- 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_69ee812a698881908d6a58265995fa39 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f61070d7348190ac0ac38a0249d2b8 |
completed | May 2, 2026, 2:55 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 11:01 p.m.