Triple
T3087774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poland, Maine |
E64413
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | West Poland, Maine |
E64413
|
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: West Poland, Maine | Statement: [Poland, Maine, hasVillage, West Poland, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: West Poland, Maine Context triple: [Poland, Maine, hasVillage, West Poland, Maine]
-
A.
Poland, Maine
chosen
Poland, Maine is a small town in southwestern Maine known for its rural character and historic Poland Spring resort and bottled water brand.
-
B.
Brownfield, Maine
Brownfield, Maine is a small rural town in western Maine known for its scenic landscapes, outdoor recreation, and proximity to the White Mountains.
-
C.
Washburn, Maine
Washburn, Maine is a small rural town in northern Maine known for its agricultural landscape and location within Aroostook County.
-
D.
Industry, Maine
Industry, Maine is a small rural town in Franklin County known for its scenic lakes, forests, and outdoor recreation.
-
E.
Strong, Maine
Strong, Maine is a small rural town in western Maine known historically for its lumber and toothpick manufacturing industries.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada209fd24819088d887de0a4158f4 |
completed | March 8, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f8a1fdc48190ae1c2fb9e5198336 |
completed | March 11, 2026, 11:20 p.m. |
Created at: March 8, 2026, 3:03 p.m.