Triple
T3870956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Dig |
E91982
|
entity |
| Predicate | trafficEffect |
P3830
|
FINISHED |
| Object | improved north–south traffic flow through 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: improved north–south traffic flow through Boston | Statement: [Big Dig, trafficEffect, improved north–south traffic flow through Boston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficEffect Context triple: [Big Dig, trafficEffect, improved north–south traffic flow through Boston]
-
A.
transportationImpact
chosen
Indicates how one entity’s transportation-related activities or characteristics affect another entity or the surrounding environment.
-
B.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
C.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
-
D.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
E.
relievesTrafficFrom
Indicates that one entity reduces or alleviates traffic congestion that would otherwise occur on another entity.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec54b0848190a8d4a0e4df7b6227 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.