Triple
T8922749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VA 234 |
E212464
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | US 29 |
E758408
|
NE 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: US 29 | Statement: [VA 234, connectsTo, US 29]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US 29 Context triple: [VA 234, connectsTo, US 29]
-
A.
US 29
chosen
US 29 is a major north–south U.S. Highway running through the eastern United States, connecting cities from Florida to Virginia and beyond.
-
B.
US 23
US 23 is a major north–south United States highway running from Florida to Michigan, serving as an important regional transportation corridor.
-
C.
US 209
US 209 is a U.S. highway running through Pennsylvania and New York, connecting rural communities, small towns, and scenic areas in the northeastern United States.
-
D.
US 27
US 27 is a major north–south United States highway running from southern Florida through several states to the Midwest.
-
E.
US 31
US 31 is a major north–south United States highway running through several Midwestern and Southern states, serving as an important regional transportation corridor.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc665143688190872c681f4299bd9f |
completed | April 1, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba5480d48190bf126caaa882d39e |
completed | April 3, 2026, 1:02 p.m. |
Created at: March 30, 2026, 6:56 p.m.