Triple
T35785148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fall Carlisle |
E1034543
|
entity |
| Predicate | regionRelevance |
P181078
|
FINISHED |
| Object | national |
—
|
LITERAL 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: national | Statement: [Fall Carlisle, regionRelevance, national]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionRelevance Context triple: [Fall Carlisle, regionRelevance, national]
-
A.
geographicRelevance
chosen
Indicates that something has a meaningful connection or applicability to a specific geographic area or location.
-
B.
regionStrength
Indicates the relative level of influence, power, or dominance that one region holds within a specified context or comparison.
-
C.
regionReveredIn
Indicates that a particular region is held in special respect, honor, or veneration within another specified area or locale.
-
D.
regionReference
Indicates that one entity refers to, points to, or is associated with a specific region or area defined by another entity.
-
E.
regionCorrespondsRoughlyTo
Indicates that one region approximately matches or aligns with another in location, extent, or boundaries, but not with precise or exact correspondence.
- 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fff328ddc0819080642334a41fcf95 |
completed | May 10, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69fff2e0971c819081aa66f4a6a34b28 |
completed | May 10, 2026, 2:52 a.m. |
Created at: May 3, 2026, 4:06 p.m.