Triple
T25070542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPE350 |
E627894
|
entity |
| Predicate | hasUnderlyingRegion |
P64159
|
FINISHED |
| Object | Europe |
—
|
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: Europe | Statement: [SPE350, hasUnderlyingRegion, Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderlyingRegion Context triple: [SPE350, hasUnderlyingRegion, Europe]
-
A.
hasUnderlyingEntity
Indicates that one entity serves as the fundamental or base entity upon which another entity is conceptually or structurally built.
-
B.
hasRegionBehind
Indicates that one region is spatially located behind another region relative to a given viewpoint or reference frame.
-
C.
hasBaseRegion
chosen
Indicates that one entity is situated upon, supported by, or primarily associated with a specific underlying region or area.
-
D.
hasUnderlyingSet
Indicates that one mathematical structure is associated with, or based on, a specific underlying set of elements.
-
E.
underliesArea
Indicates that one entity forms the foundational basis or underlying support for a particular area or domain of activity, knowledge, or influence.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 18, 2026, 6:10 a.m.