Triple
T7247453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R5 Lansdale/Doylestown |
E156510
|
entity |
| Predicate | formerRouteNumber |
P22310
|
FINISHED |
| Object | R5 |
E628681
|
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: R5 | Statement: [R5 Lansdale/Doylestown, formerRouteNumber, R5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R5 Context triple: [R5 Lansdale/Doylestown, formerRouteNumber, R5]
-
A.
R5
R5 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
-
B.
R5
R5 is the U.S. Forest Service’s Pacific Southwest Region, which oversees national forests primarily in California and parts of neighboring areas.
-
C.
R5
chosen
R5 was a former designation for a commuter rail line in the SEPTA Regional Rail system serving the Paoli/Thorndale corridor in the Philadelphia area.
-
D.
R55
R55 is a regional road in South Africa that runs through Gauteng, connecting areas such as Midrand with surrounding suburbs and major routes.
-
E.
R-5
The R-5 is an early Sikorsky military helicopter developed during World War II, known for advancing rotary-wing design and serving in roles such as rescue and liaison.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea749fb08190841c0aa8c5bd0727 |
completed | March 27, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d39dab6081909842bfa37ff3f972 |
completed | March 28, 2026, 1:11 p.m. |
Created at: March 27, 2026, 2:56 p.m.