Triple
T12026568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green–Tao theorem |
E286292
|
entity |
| Predicate | firstPreprint |
P15299
|
FINISHED |
| Object | arXiv:math/0404188 |
—
|
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: arXiv:math/0404188 | Statement: [Green–Tao theorem, firstPreprint, arXiv:math/0404188]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPreprint Context triple: [Green–Tao theorem, firstPreprint, arXiv:math/0404188]
-
A.
firstPublicationIn
Indicates the initial venue, medium, or context in which a work was first published.
-
B.
initialPublication
chosen
Indicates the relationship in which a work is first formally published or made publicly available.
-
C.
firstPublishedWith
Indicates that an entity was initially published together with another specified entity, sharing the same first publication event.
-
D.
firstDraftPublishedIn
Indicates that the first draft of a work was published or made publicly available in a specified venue, medium, or publication.
-
E.
first
Indicates that one entity precedes all others in an ordered sequence or ranking.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902b6ebbc8190b13c44a61c6f81b9 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.