Triple
T17410742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarborough station |
E423349
|
entity |
| Predicate | distanceToGrandCentralTerminal |
P38946
|
FINISHED |
| Object | approximately 28 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 28 miles | Statement: [Scarborough station, distanceToGrandCentralTerminal, approximately 28 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGrandCentralTerminal Context triple: [Scarborough station, distanceToGrandCentralTerminal, approximately 28 miles]
-
A.
distanceFromGrandCentral
chosen
Indicates the spatial distance between a given entity and Grand Central.
-
B.
distanceFromPennStation
Indicates the physical distance between a given location and Penn Station.
-
C.
distanceFromSouthStation
Indicates the measured distance between a given location or entity and South Station.
-
D.
distanceFromStation
Indicates the measured spatial separation between an entity and a specified station.
-
E.
distanceFromStPancras
Indicates the spatial distance between an entity and St Pancras.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b0a88e881909b2886bd90c92992 |
completed | April 19, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.