Triple
T37254283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paupack, Pennsylvania |
E924080
|
entity |
| Predicate | locatedOnOrNearRoute |
P86982
|
FINISHED |
| Object | Pennsylvania Route 507 |
E1363270
|
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: Pennsylvania Route 507 | Statement: [Paupack, Pennsylvania, locatedOnOrNearRoute, Pennsylvania Route 507]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedOnOrNearRoute Context triple: [Paupack, Pennsylvania, locatedOnOrNearRoute, Pennsylvania Route 507]
-
A.
locatedOnRouteTo
Indicates that one entity lies along the path or course taken when traveling from a starting point to a specified destination.
-
B.
situatedOnTransportRoute
chosen
Indicates that one entity is located along, on, or directly adjacent to a specified transport route (such as a road, railway, or shipping lane).
-
C.
nearJunctionOf
Indicates that one entity is located close to the point where two or more linear features (such as roads, tracks, or paths) meet or intersect.
-
D.
locatedOnTrekkingRoute
Indicates that something is situated along or directly on a designated trekking or hiking route.
-
E.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
- F. None of above.
Provenance (4 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_69f76eaabb4c819093b751b139dad551 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a79c22708f88190b334b723c44435dd |
completed | Aug. 10, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.