Triple
T20153968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Infrastructure |
E491505
|
entity |
| Predicate | isOftenProvidedBy |
P65734
|
FINISHED |
| Object | Governments |
—
|
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: Governments | Statement: [Infrastructure, isOftenProvidedBy, Governments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenProvidedBy Context triple: [Infrastructure, isOftenProvidedBy, Governments]
-
A.
oftenProvides
chosen
Indicates that one entity frequently or regularly supplies, offers, or makes another entity available.
-
B.
isOftenRequiredFor
Indicates that one entity is frequently needed or commonly necessary for the occurrence, use, or success of another entity or activity.
-
C.
isFrequentlyProducedBy
Indicates that something is commonly or regularly generated, created, or brought about by a particular entity or source.
-
D.
mayProvideFor
Indicates that one entity is permitted or has the option to supply, support, or otherwise furnish something for another entity.
-
E.
isFrequentlyIncludedIn
Indicates that something is regularly or commonly contained or made part of something else.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667de9bec8190836887c86dbcf28d |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.