Triple
T15032087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US 1 |
E378377
|
entity |
| Predicate | passesThroughState |
P3448
|
FINISHED |
| Object | Maine |
E29256
|
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: Maine | Statement: [US 1, passesThroughState, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maine Context triple: [US 1, passesThroughState, Maine]
-
A.
Maine
chosen
Maine is a northeastern U.S. state known for its rugged coastline, maritime history, and vast forested interior.
-
B.
Maine
Maine is a historical region in northwestern France that played a significant role in the medieval power struggles between the English and French crowns.
-
C.
Maine
Maine is an American rapper, songwriter, and record executive best known as the president of Young Money Entertainment.
-
D.
New Hampshire and Maine
New Hampshire and Maine are neighboring New England states in the northeastern United States, known for their rugged coastlines, forested landscapes, and historic colonial towns.
-
E.
Freedom, Maine
Freedom, Maine is a small rural town in central Maine known for its scenic countryside and tight-knit community.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e2416081908dfba48d7f7b4a84 |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7d956808190a3f17ef14c21d3af |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 2:59 a.m.