Triple
T10537121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lansdowne, Pennsylvania |
E248594
|
entity |
| Predicate | distanceToPhiladelphiaCenter |
P2384
|
FINISHED |
| Object | approximately 6 miles west |
—
|
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: approximately 6 miles west | Statement: [Lansdowne, Pennsylvania, distanceToPhiladelphiaCenter, approximately 6 miles west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPhiladelphiaCenter Context triple: [Lansdowne, Pennsylvania, distanceToPhiladelphiaCenter, approximately 6 miles west]
-
A.
distanceToPhiladelphia
chosen
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
-
B.
distanceToHarrisburg
Indicates the spatial distance between a given entity and the location of Harrisburg.
-
C.
distanceToPittsburgh
Indicates the spatial distance between a given entity’s location and the city of Pittsburgh.
-
D.
distanceFromPennStation
Indicates the physical distance between a given location and Penn Station.
-
E.
distanceToPennsylvaniaBorder
Indicates the measured distance between a given location and the border of Pennsylvania.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a554fb4819081e9618bab051dc6 |
completed | April 7, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69d4fb9729288190a0149f127acd7ae3 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:31 p.m.