Triple
T4441564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston beltway system |
E95781
|
entity |
| Predicate | notableJunction |
P31669
|
FINISHED |
| Object | I-95 and I-93 interchange |
—
|
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: I-95 and I-93 interchange | Statement: [Boston beltway system, notableJunction, I-95 and I-93 interchange]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableJunction Context triple: [Boston beltway system, notableJunction, I-95 and I-93 interchange]
-
A.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
B.
notableRouteFeature
Indicates that a route is associated with a distinctive or significant feature, such as a landmark, characteristic terrain, or other notable aspect along its path.
-
C.
notableRouteType
Indicates that a route is particularly significant or well-known for a specific type or category (e.g., scenic, historic, commercial).
-
D.
notableInCity
Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
-
E.
nearJunctionOf
chosen
Indicates that one entity is located close to the point where two or more linear features (such as roads, tracks, or paths) meet or intersect.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355ad71588190b1dcad4250472c29 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.