Triple
T12150242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothy Arnold |
E289432
|
entity |
| Predicate | caseClassification |
P81213
|
FINISHED |
| Object | unsolved missing-person case |
—
|
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: unsolved missing-person case | Statement: [Dorothy Arnold, caseClassification, unsolved missing-person case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseClassification Context triple: [Dorothy Arnold, caseClassification, unsolved missing-person case]
-
A.
caseTypes
chosen
Indicates the types or categories of cases associated with or applicable to an entity or situation.
-
B.
doctrineClassification
Indicates how a particular doctrine is categorized or classified within a defined system of doctrinal types.
-
C.
classificationAccordingTo
Indicates that an entity is assigned a particular class, type, or category as defined or determined by a specified source, standard, or authority.
-
D.
classificationIssue
Indicates that there is a problem, ambiguity, or error in how something has been categorized or assigned to a class or type.
-
E.
classificationLetter
Indicates that an entity is assigned a specific letter-based category or grade as its classification.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.