Triple
T7631152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy U.S. Marshal Samuel Gerard |
E172760
|
entity |
| Predicate | pursuesCrimeType |
P77441
|
FINISHED |
| Object | murder fugitive |
—
|
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: murder fugitive | Statement: [Deputy U.S. Marshal Samuel Gerard, pursuesCrimeType, murder fugitive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pursuesCrimeType Context triple: [Deputy U.S. Marshal Samuel Gerard, pursuesCrimeType, murder fugitive]
-
A.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
B.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
-
D.
hasCrimeInvestigation
Indicates that an entity is the subject of, or associated with, a formal investigation into a crime.
-
E.
recognitionOfCrimes
Indicates the formal acknowledgment or identification that certain actions or events constitute crimes under a legal or normative framework.
- F. None of above. chosen
Provenance (4 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faa4d2808190942129110711788b |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f574d8a8819095749518dad13791 |
completed | March 27, 2026, 9:24 p.m. |
Created at: March 27, 2026, 3:56 p.m.