Triple
T7201476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peru, Maine |
E168754
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Mexico, Maine |
E97307
|
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: Mexico, Maine | Statement: [Peru, Maine, adjacentTo, Mexico, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mexico, Maine Context triple: [Peru, Maine, adjacentTo, Mexico, Maine]
-
A.
Mexico, Maine
chosen
Mexico, Maine is a small town in Oxford County known historically as a mill and residential community closely linked with the neighboring industrial town of Rumford.
-
B.
Peru, Maine
Peru, Maine is a small rural town in Oxford County known for its scenic western Maine landscape and close-knit community.
-
C.
Maine
Maine is a northeastern U.S. state known for its rugged coastline, maritime history, and vast forested interior.
-
D.
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.
-
E.
Cuba, New Mexico
Cuba, New Mexico is a small village in northwestern New Mexico that serves as a gateway community to the nearby Jemez Mountains and several Native American reservations.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94971508190bb38184c9af2fe51 |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfb0f4688190a677b818a0b3619c |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:52 p.m.