Triple
T31827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princeton, New Jersey, United States |
E634
|
entity |
| Predicate | distanceToNewYorkCity |
P2383
|
FINISHED |
| Object | about 50 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: about 50 miles | Statement: [Princeton, New Jersey, United States, distanceToNewYorkCity, about 50 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNewYorkCity Context triple: [Princeton, New Jersey, United States, distanceToNewYorkCity, about 50 miles]
-
A.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
-
B.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
C.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
D.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
E.
isLargestCityIn
Indicates that one city has the greatest population or size compared to all other cities within a specified region or administrative area.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a249ec0d288190ac3a0939db61813b |
completed | Feb. 28, 2026, 1:50 a.m. |
| PD | Predicate disambiguation | batch_69a24870417081909c7c01e400c94716 |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a249eb52a08190916849b44bd9d68d |
completed | Feb. 28, 2026, 1:50 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.