Triple
T4952658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middlesex County Sheriff’s Office |
E111203
|
entity |
| Predicate | hasTypeOfAgency |
P3504
|
FINISHED |
| Object | county sheriff’s office |
—
|
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: county sheriff’s office | Statement: [Middlesex County Sheriff’s Office, hasTypeOfAgency, county sheriff’s office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfAgency Context triple: [Middlesex County Sheriff’s Office, hasTypeOfAgency, county sheriff’s office]
-
A.
hasTypeOfOrganization
chosen
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
B.
hasKeyAgency
Indicates that an entity serves as the primary responsible or controlling agency for another entity, action, or process.
-
C.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
D.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
-
E.
hasAgent
Indicates that an action or event is carried out or initiated by a particular agent.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71b6a5d481909ad6f5e0b752496c |
completed | March 20, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.