Triple
T8733498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasse bound for elliptic curves |
E207314
|
entity |
| Predicate | isTight |
P84549
|
FINISHED |
| Object | yes, bounds are best possible in general |
—
|
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: yes, bounds are best possible in general | Statement: [Hasse bound for elliptic curves, isTight, yes, bounds are best possible in general]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTight Context triple: [Hasse bound for elliptic curves, isTight, yes, bounds are best possible in general]
-
A.
isNarrow
Indicates that something has a small width or limited breadth relative to a reference or context.
-
B.
isT1
Indicates that one entity is classified or designated as type T1 in relation to another entity or context.
-
C.
isShort
Indicates that one entity has a relatively small height, length, or duration compared to a standard or to other entities.
-
D.
isCompact
Indicates that an object or space has a small, efficiently arranged size or volume relative to its function or contents.
-
E.
isSmall
Indicates that one entity has a size that is relatively small, either in absolute terms or compared to a reference standard or another entity.
- F. None of above. chosen
Provenance (4 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d2a26988190acfda17f232e610a |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457322b481908712a9630a17b954 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:37 p.m.