Triple
T17640532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union County jail |
E429211
|
entity |
| Predicate | typicalSentenceLength |
P11478
|
FINISHED |
| Object | less than one year |
—
|
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: less than one year | Statement: [Union County jail, typicalSentenceLength, less than one year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSentenceLength Context triple: [Union County jail, typicalSentenceLength, less than one year]
-
A.
sentenceLength
Indicates the length or number of units (such as characters, words, or tokens) that a given sentence contains.
-
B.
typicalSentenceRange
chosen
Indicates the usual or most common range of sentence lengths (e.g., in years or months) typically imposed for a given offense or legal category.
-
C.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
D.
wordLength
Indicates that there is a relationship specifying the number of characters (length) in a given word.
-
E.
typicalPositionInSentence
Indicates the usual or most common position that an element occupies within the linear order of components in a sentence.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de50bf481909e938613b38f0202 |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 6:02 a.m.