Triple
T15088837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin County, Maine |
E360357
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Industry, Maine |
E62819
|
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: Industry, Maine | Statement: [Franklin County, Maine, contains, Industry, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Industry, Maine Context triple: [Franklin County, Maine, contains, Industry, Maine]
-
A.
Industry, Maine
chosen
Industry, Maine is a small rural town in Franklin County known for its scenic lakes, forests, and outdoor recreation.
-
B.
Gray, Maine
Gray, Maine is a small New England town in southern Maine known for its rural character, proximity to Portland, and the Maine Wildlife Park.
-
C.
Hope, Maine
Hope, Maine is a small rural town in coastal Knox County known for its scenic lakes, rolling hills, and quiet New England character.
-
D.
Strong, Maine
Strong, Maine is a small rural town in western Maine known historically for its lumber and toothpick manufacturing industries.
-
E.
Mercer, Maine
Mercer, Maine is a small rural town located in Somerset County in the central part of the state.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00277ea808190be3f002a8316eff1 |
completed | April 15, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae1ba4208190b1e8c55668a1b422 |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:04 a.m.