Triple
T19766977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AM |
E474783
|
entity |
| Predicate | appliesToRegionType |
P137247
|
FINISHED |
| Object | administrative region |
—
|
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: administrative region | Statement: [AM, appliesToRegionType, administrative region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToRegionType Context triple: [AM, appliesToRegionType, administrative region]
-
A.
containsRegionType
Indicates that one region includes or encompasses another region of a specified type within its spatial or logical boundaries.
-
B.
supportsRegion
Indicates that one entity provides assistance, resources, or backing to a specific geographic or administrative region.
-
C.
hasTypicalUsageRegion
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
D.
appliesToServiceType
Indicates that something is relevant or applicable specifically to a particular type or category of service.
-
E.
operatesToRegion
Indicates that an agent conducts operations or provides services directed toward or within a specified region.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653232e508190a7d484c0a1e2939a |
completed | April 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:48 p.m.