Triple
T356932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangor metropolitan area |
E7564
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Old Town, Maine
Old Town, Maine is a small city in Penobscot County known for its historic paper and wood-products industries and its location along the Penobscot River.
|
E66161
|
NE FINISHED |
How this triple was built (4 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: Old Town, Maine | Statement: [Bangor metropolitan area, contains, Old Town, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Old Town, Maine Context triple: [Bangor metropolitan area, contains, Old Town, Maine]
-
A.
Harrison, Maine
Harrison, Maine is a small town in western Maine known for its lakeside setting and recreational opportunities in Oxford County.
-
B.
Newport, Maine
Newport, Maine is a small town in Penobscot County known as a regional service and transportation hub in central Maine.
-
C.
Temple, Maine
Temple, Maine is a small rural town in western Maine known for its forested landscape and quiet, close-knit community.
-
D.
Lovell, Maine
Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
-
E.
Avon, Maine
Avon, Maine is a small rural town in western Maine known for its scenic landscapes and location within Franklin County.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Old Town, Maine Triple: [Bangor metropolitan area, contains, Old Town, Maine]
Generated description
Old Town, Maine is a small city in Penobscot County known for its historic paper and wood-products industries and its location along the Penobscot River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Old Town, Maine Target entity description: Old Town, Maine is a small city in Penobscot County known for its historic paper and wood-products industries and its location along the Penobscot River.
-
A.
Harrison, Maine
Harrison, Maine is a small town in western Maine known for its lakeside setting and recreational opportunities in Oxford County.
-
B.
Newport, Maine
Newport, Maine is a small town in Penobscot County known as a regional service and transportation hub in central Maine.
-
C.
Temple, Maine
Temple, Maine is a small rural town in western Maine known for its forested landscape and quiet, close-knit community.
-
D.
Lovell, Maine
Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
-
E.
Avon, Maine
Avon, Maine is a small rural town in western Maine known for its scenic landscapes and location within Franklin County.
- F. None of above. chosen
Provenance (5 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebaf0c9881909313f98818e7fa58 |
completed | Feb. 28, 2026, 1:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4b5d217dc8190b5b751e94f44a841 |
completed | March 1, 2026, 9:55 p.m. |
| NEDg | Description generation | batch_69a4b673f5dc8190a70b7ddcf76ec016 |
completed | March 1, 2026, 9:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4b79ec4b48190b992f642aa7cddb7 |
completed | March 1, 2026, 10:03 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.