Triple
T9979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynn |
E202
|
entity |
| Predicate | distanceFromBoston |
P798
|
FINISHED |
| Object | about 10 miles northeast of downtown Boston |
—
|
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 10 miles northeast of downtown Boston | Statement: [Lynn, distanceFromBoston, about 10 miles northeast of downtown Boston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBoston Context triple: [Lynn, distanceFromBoston, about 10 miles northeast of downtown Boston]
-
A.
cityAtMouth
Indicates that a city is located at or very near the mouth (outlet) of a river.
-
B.
hasMajorAirport
Indicates that a location possesses at least one significant airport that serves as a primary hub for air travel in that area.
-
C.
partOfMetropolitanArea
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
-
D.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
E.
isPortCityOn
Indicates that a city functions as a port located on the specified body of water.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a240b249788190af8dbf7e80e9c91b |
completed | Feb. 28, 2026, 1:11 a.m. |
| PD | Predicate disambiguation | batch_69a23fe52ec48190a4d24101c91434ed |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a240b1551c81908abcae128ea45d00 |
completed | Feb. 28, 2026, 1:11 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.