Triple
T4979433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lock Haven, Pennsylvania |
E111846
|
entity |
| Predicate | distanceFromMajorCity |
P60767
|
FINISHED |
| Object | approximately 30 miles west of Williamsport |
—
|
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 30 miles west of Williamsport | Statement: [Lock Haven, Pennsylvania, distanceFromMajorCity, approximately 30 miles west of Williamsport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMajorCity Context triple: [Lock Haven, Pennsylvania, distanceFromMajorCity, approximately 30 miles west of Williamsport]
-
A.
nearestMajorCity
Indicates that one city is the closest significant urban center to another location or city compared to all other major cities.
-
B.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
C.
distanceFromLosAngeles
Indicates the measured or specified distance between a given entity’s location and the city of Los Angeles.
-
D.
otherMajorCity
Indicates that one city is another major city associated with or comparable in importance or status to the first city.
-
E.
distanceToLosAngeles
Indicates the measured or calculated distance between a given entity’s location and the city of Los Angeles.
- F. None of above. chosen
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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:33 p.m.