Triple
T12501912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bladensburg Police Department |
E298846
|
entity |
| Predicate | serviceAreaPopulationType |
P93194
|
FINISHED |
| Object | local residents |
—
|
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: local residents | Statement: [Bladensburg Police Department, serviceAreaPopulationType, local residents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceAreaPopulationType Context triple: [Bladensburg Police Department, serviceAreaPopulationType, local residents]
-
A.
servicePopulationType
chosen
Indicates the type or category of population that a service is intended to serve or target.
-
B.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
-
C.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
-
D.
hadPopulationType
Indicates that an entity possessed a particular classification or type of population during a given time or context.
-
E.
hostedPopulationType
Indicates the type or category of population that is accommodated or supported by a given host entity.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:57 p.m.