Triple
T28220276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Chamberlain (Maine poet) |
E711434
|
entity |
| Predicate | hasRegionAsSubject |
P79706
|
FINISHED |
| Object | Maine |
—
|
NE NERFINISHED |
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: Maine | Statement: [John Chamberlain (Maine poet), hasRegionAsSubject, Maine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionAsSubject Context triple: [John Chamberlain (Maine poet), hasRegionAsSubject, Maine]
-
A.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
B.
isRegionOf
Indicates that one entity is a geographic or administrative region belonging to, contained within, or associated with another entity.
-
C.
hasSubjectPlace
chosen
Indicates that something is associated with or occurs in a particular subject-related place or location.
-
D.
hasRegionalEntity
Indicates that one entity includes, governs, or is associated with another entity that functions as its regional subdivision or component.
-
E.
hasSubregionRelationWith
Indicates a relationship where one region is a subregion or contained part of another region.
- F. None of above.
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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ff3b32ee148190a3ba3b7600943fef |
completed | May 9, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69ff3a238af88190a2c2245e30299e48 |
completed | May 9, 2026, 1:44 p.m. |
Created at: April 27, 2026, 10:46 p.m.