Triple
T34553626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Lyons |
E887140
|
entity |
| Predicate | notableIdea |
P4
|
FINISHED |
| Object | systematic introduction of semantics into general linguistics curricula |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: systematic introduction of semantics into general linguistics curricula | Statement: [John Lyons, notableIdea, systematic introduction of semantics into general linguistics curricula]
Provenance (2 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72029a73c8190ac6969098273c1eb |
completed | May 3, 2026, 10:15 a.m. |
Created at: May 1, 2026, 2:02 a.m.