Triple
T26775959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary Duncan |
E670119
|
entity |
| Predicate | sentenceReceived |
P14999
|
FINISHED |
| Object | $150 fine |
—
|
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: $150 fine | Statement: [Gary Duncan, sentenceReceived, $150 fine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceReceived Context triple: [Gary Duncan, sentenceReceived, $150 fine]
-
A.
receivedSentence
chosen
Indicates that one entity has been given or accepted a sentence (such as a legal punishment or formal judgment) from another entity or authority.
-
B.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
C.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
D.
receives
Indicates that one entity is the recipient of something (such as an object, message, or action) from another entity.
-
E.
sentenceType
Indicates the classification of a sentence according to its communicative function or structural type (e.g., question, statement, command).
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6193294948190adeecbad17283103 |
completed | May 2, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:04 a.m.