Triple
T8168310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manhasset station |
E190750
|
entity |
| Predicate | distanceToPennStation |
P43953
|
FINISHED |
| Object | approximately 17 miles |
—
|
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 17 miles | Statement: [Manhasset station, distanceToPennStation, approximately 17 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPennStation Context triple: [Manhasset station, distanceToPennStation, approximately 17 miles]
-
A.
distanceFromPennStation
chosen
Indicates the physical distance between a given location and Penn Station.
-
B.
distanceFromGrandCentral
Indicates the spatial distance between a given entity and Grand Central.
-
C.
distanceToPoughkeepsie
Indicates the spatial distance between a given entity and the location of Poughkeepsie.
-
D.
distanceFromStation
Indicates the measured spatial separation between an entity and a specified station.
-
E.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
- 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_69ca82c0ef14819083713f4473dd847c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb466abfe48190b4eb2f23b1e28668 |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:39 p.m.