Triple
T9793926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 216 (unused number) |
E237670
|
entity |
| Predicate | hasExitNumbers |
P87730
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Interstate 216 (unused number), hasExitNumbers, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExitNumbers Context triple: [Interstate 216 (unused number), hasExitNumbers, none]
-
A.
hasNumberOfExits
chosen
Indicates the relationship that specifies how many exits are associated with a given entity.
-
B.
exitsThrough
Indicates that an entity leaves or departs from a place, structure, or area by passing through a specified exit or passage.
-
C.
hasConnectingRoadNumber
Indicates that there exists a road connection between two locations or road segments identified by a specific road number.
-
D.
hasExitFor
Indicates that something provides or includes a specific exit intended for a particular destination, purpose, or user.
-
E.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
- 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_69ca84dc04488190b9c91193976c0960 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda347b6bc8190a99b7dec1650cd46 |
completed | April 1, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69cd03da45a88190b71b1be3354c15a6 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:28 p.m.