Triple
T22343422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crime in the United States |
E552330
|
entity |
| Predicate | coversStatistic |
P110931
|
FINISHED |
| Object | violent crime |
—
|
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: violent crime | Statement: [Crime in the United States, coversStatistic, violent crime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversStatistic Context triple: [Crime in the United States, coversStatistic, violent crime]
-
A.
statisticsConsidered
Indicates that certain statistics are taken into account or used as a basis in a decision, analysis, or evaluation involving the related entities.
-
B.
hasStatistics
Indicates that an entity is associated with one or more statistical measures, records, or summaries describing its quantitative properties or performance.
-
C.
statisticNote
Indicates that there is an explanatory note or comment providing additional context or clarification about a reported statistic.
-
D.
statisticalScope
chosen
Indicates the statistical context or coverage within which a given measurement, observation, or statement is defined or valid.
-
E.
usedInStatistic
Indicates that something (such as a value, measure, or data item) is employed as part of the calculation or presentation of a particular statistic.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15795b2a881908d6cb8f97443ca17 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.