Triple
T13507891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coolsville |
E321058
|
entity |
| Predicate | hasCrimeRate |
P90045
|
FINISHED |
| Object | unusually high rate of mystery-related incidents |
—
|
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: unusually high rate of mystery-related incidents | Statement: [Coolsville, hasCrimeRate, unusually high rate of mystery-related incidents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrimeRate Context triple: [Coolsville, hasCrimeRate, unusually high rate of mystery-related incidents]
-
A.
crimeRate
chosen
Indicates the frequency or level of criminal activity occurring within a given area or population.
-
B.
hasCrimeElement
Indicates that a situation, action, or entity involves or contains a component that is legally recognized as part of a crime.
-
C.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
D.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
E.
haveCriminalLaw
Indicates that an entity possesses, applies, or is governed by a system or body of criminal law.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf85a74081909eb08751fc55ce8f |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:43 p.m.