Triple
T28371499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Hill Historical Society |
E718646
|
entity |
| Predicate | hasAreaOfBenefit |
P101823
|
FINISHED |
| Object | Blue Hill, 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: Blue Hill, Maine | Statement: [Blue Hill Historical Society, hasAreaOfBenefit, Blue Hill, Maine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaOfBenefit Context triple: [Blue Hill Historical Society, hasAreaOfBenefit, Blue Hill, Maine]
-
A.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
benefitsArea
chosen
Indicates that one entity provides advantages, improvements, or positive effects to a specified area or region.
-
C.
hasAreaOfCoverage
Indicates that an entity provides services, influence, or applicability within a specified geographic or conceptual region.
-
D.
hasImpactArea
Indicates that an entity affects, influences, or has consequences within a specific area, domain, or scope.
-
E.
affectsBenefit
Indicates that one entity has an influence on, modifies, or determines the benefit or advantage received by another entity.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 28, 2026, 1 a.m.