Triple
T7582241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PGFD/EMS |
E179514
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | PGFD/EMS |
E179514
|
NE 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: PGFD/EMS | Statement: [PGFD/EMS, hasAbbreviation, PGFD/EMS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PGFD/EMS Context triple: [PGFD/EMS, hasAbbreviation, PGFD/EMS]
-
A.
PGFD/EMS
chosen
PGFD/EMS is the combined fire protection and emergency medical services agency serving Prince George’s County, Maryland.
-
B.
PGFD
PGFD is the fire and emergency medical services agency serving Prince George’s County, Maryland.
-
C.
DCFEMS
DCFEMS is the primary fire protection and emergency medical services agency serving Washington, D.C.
-
D.
EMS
EMS is an emergency medical services organization that provides pre-hospital care and ambulance transport in response to medical emergencies.
-
E.
EMS
EMS is the vehicle registration code used on license plates for vehicles registered in the district of Rhein-Lahn-Kreis, whose administrative seat is Nassau, in the German state of Rhineland-Palatinate.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f327db881909a21ae3b156f8ded |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f978341081909e009c410ffc5039 |
completed | March 27, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8617b8934819094f596e6a037e468 |
completed | March 28, 2026, 11:17 p.m. |
Created at: March 27, 2026, 3:52 p.m.