Triple
T17856348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forestville, Maryland |
E445946
|
entity |
| Predicate | federalGovernmentPresenceNearby |
P80106
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Forestville, Maryland, federalGovernmentPresenceNearby, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: federalGovernmentPresenceNearby Context triple: [Forestville, Maryland, federalGovernmentPresenceNearby, high]
-
A.
nearbyFederalAgency
Indicates that one federal agency is located geographically close to another federal agency.
-
B.
governingBodyNearby
Indicates that a governing body is located in close physical proximity to the referenced entity or area.
-
C.
nearbyPoliticalEntity
chosen
Indicates that one political entity is geographically close to another political entity, without necessarily sharing a border.
-
D.
usesGovernmentBuilding
Indicates that an entity makes use of a government-owned or government-operated building for some purpose or activity.
-
E.
isGovernmentFacility
Indicates that the subject entity functions as a facility owned, operated, or officially designated for use by a government or its agencies.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978bd5e081909e192f6aada5235f |
completed | April 19, 2026, 8:51 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:17 a.m.