Triple
T4077170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SOFIA |
E87390
|
entity |
| Predicate | typeOfStatistics |
P40641
|
FINISHED |
| Object | production statistics |
—
|
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: production statistics | Statement: [SOFIA, typeOfStatistics, production statistics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfStatistics Context triple: [SOFIA, typeOfStatistics, production statistics]
-
A.
statisticsType
Indicates the specific kind or category of statistical measure or analysis associated with an entity or dataset.
-
B.
statisticalType
chosen
Indicates that one entity specifies the kind or category of statistical characterization or measurement that applies to another entity.
-
C.
hasStatistics
Indicates that an entity is associated with one or more statistical measures, records, or summaries describing its quantitative properties or performance.
-
D.
statisticsConsidered
Indicates that certain statistics are taken into account or used as a basis in a decision, analysis, or evaluation involving the related entities.
-
E.
statisticalUnitOf
Indicates that one entity serves as the statistical unit (the basic unit of observation or analysis) for which data or statistics are collected or reported about another entity.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc4d348c8190a94724639830aca0 |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.