Triple
T10310954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meriden station |
E241886
|
entity |
| Predicate | distanceFromNewHaven |
P93308
|
FINISHED |
| Object | approximately 21 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 21 miles | Statement: [Meriden station, distanceFromNewHaven, approximately 21 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNewHaven Context triple: [Meriden station, distanceFromNewHaven, approximately 21 miles]
-
A.
distanceToHartford
Indicates the spatial distance between a given entity’s location and the city of Hartford.
-
B.
distanceToStamford
Indicates the spatial distance between a given entity and the location Stamford.
-
C.
distanceToProvidence
Indicates the measured spatial distance between a given entity’s location and the location of Providence.
-
D.
distanceFromWestport
Indicates the measured distance between a given location and the reference place named Westport.
-
E.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:47 a.m.