Triple
T17517745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tranquility |
E426607
|
entity |
| Predicate | primaryRegionCoverage |
P117752
|
FINISHED |
| Object | global excluding mainland China |
—
|
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: global excluding mainland China | Statement: [Tranquility, primaryRegionCoverage, global excluding mainland China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRegionCoverage Context triple: [Tranquility, primaryRegionCoverage, global excluding mainland China]
-
A.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
B.
primaryCoverage
Indicates that one entity serves as the main or principal source of coverage (such as insurance or protection) for another entity.
-
C.
dataCoverage
Indicates the extent or proportion of relevant data that is included, captured, or represented within a given dataset or system.
-
D.
primaryRegionRepresented
Indicates the main geographic or administrative region that an entity officially represents or speaks for.
-
E.
geographicCoverageType
chosen
Indicates the type or nature of the geographic area that something covers or applies to.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452615a8481909974e9855ea7a8e4 |
completed | April 19, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.