Triple
T24807003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermat's spiral |
E620680
|
entity |
| Predicate | usedInConstruction |
P64282
|
FINISHED |
| Object | low-discrepancy point sets on the plane |
—
|
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: low-discrepancy point sets on the plane | Statement: [Fermat's spiral, usedInConstruction, low-discrepancy point sets on the plane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInConstruction Context triple: [Fermat's spiral, usedInConstruction, low-discrepancy point sets on the plane]
-
A.
constructionUsed
chosen
Indicates that one entity was employed as a construction method, material, or component in creating or assembling another entity.
-
B.
constructionUses
Indicates that a construction activity, project, or structure makes use of a specified material, method, tool, or resource.
-
C.
usedOnBuildingOf
Indicates that something is applied to, installed on, or otherwise utilized on the structure of a particular building.
-
D.
usedInStructure
Indicates that something (such as a material, component, or element) is employed as part of the composition or construction of a larger structure.
-
E.
usedInIndustry
Indicates that something is employed or applied within a particular industry or industrial sector.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 4:50 a.m.