Triple
T32672449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electronic Communications in Probability |
E835332
|
entity |
| Predicate | focus |
P31
|
FINISHED |
| Object | rapid publication of short papers in probability |
—
|
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: rapid publication of short papers in probability | Statement: [Electronic Communications in Probability, focus, rapid publication of short papers in probability]
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_69f3493134b48190aa3c8cb523bd3800 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c7aed2888190ac2feb5f1a80ef43 |
completed | May 3, 2026, 3:57 a.m. |
Created at: May 1, 2026, 1:09 a.m.