Triple
T517313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Androscoggin County, Maine |
E10735
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lisbon, Maine
Lisbon, Maine is a small town in Androscoggin County known for its historic mill heritage and annual Moxie Festival celebrating the iconic soft drink.
|
E187146
|
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: Lisbon, Maine | Statement: [Androscoggin County, Maine, contains, Lisbon, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisbon, Maine Context triple: [Androscoggin County, Maine, contains, Lisbon, Maine]
-
A.
Plymouth, Maine
Plymouth, Maine is a small rural town in Penobscot County known for its quiet residential character and forested, lake-dotted landscape.
-
B.
Solon, Maine
Solon, Maine is a small rural town in central Maine known for its scenic Kennebec River setting and outdoor recreation opportunities.
-
C.
Cambridge, Maine
Cambridge, Maine is a small rural town in central Maine known for its quiet, forested landscape and location within Somerset County.
-
D.
Avon, Maine
Avon, Maine is a small rural town in western Maine known for its scenic landscapes and location within Franklin County.
-
E.
Charleston, Maine
Charleston, Maine is a small rural town in Penobscot County known for its quiet countryside and agricultural character.
- 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: Lisbon, Maine Triple: [Androscoggin County, Maine, contains, Lisbon, Maine]
Generated description
Lisbon, Maine is a small town in Androscoggin County known for its historic mill heritage and annual Moxie Festival celebrating the iconic soft drink.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lisbon, Maine Target entity description: Lisbon, Maine is a small town in Androscoggin County known for its historic mill heritage and annual Moxie Festival celebrating the iconic soft drink.
-
A.
Plymouth, Maine
Plymouth, Maine is a small rural town in Penobscot County known for its quiet residential character and forested, lake-dotted landscape.
-
B.
Solon, Maine
Solon, Maine is a small rural town in central Maine known for its scenic Kennebec River setting and outdoor recreation opportunities.
-
C.
Cambridge, Maine
Cambridge, Maine is a small rural town in central Maine known for its quiet, forested landscape and location within Somerset County.
-
D.
Avon, Maine
Avon, Maine is a small rural town in western Maine known for its scenic landscapes and location within Franklin County.
-
E.
Charleston, Maine
Charleston, Maine is a small rural town in Penobscot County known for its quiet countryside and agricultural character.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f19d81d48190bd65a02059fc8473 |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad67e82a2481909f6d2737f820121a |
completed | March 8, 2026, 12:13 p.m. |
| NEDg | Description generation | batch_69ad68895550819080fdc84d77201e60 |
completed | March 8, 2026, 12:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad6902cb3c8190ba36dc74e1dccb26 |
completed | March 8, 2026, 12:18 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.