Triple
T8083431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuttall |
E188671
|
entity |
| Predicate | usedByProfessionalsIn |
P11801
|
FINISHED |
| Object | science |
—
|
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: science | Statement: [Nuttall, usedByProfessionalsIn, science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByProfessionalsIn Context triple: [Nuttall, usedByProfessionalsIn, science]
-
A.
usedInWork
Indicates that something (such as a concept, method, material, or component) is employed or applied within a particular work, project, or creation.
-
B.
usedInECommerce
Indicates that something is employed or applied within the context of electronic commerce activities or systems.
-
C.
usedInIndustry
Indicates that something is employed or applied within a particular industry or industrial sector.
-
D.
usedByManufacturer
Indicates that a manufacturer makes use of a particular resource, component, method, or tool in its production or operational processes.
-
E.
widelyUsedIn
chosen
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb415cb4688190920868317e77bbff |
completed | March 31, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.