Triple
T38555287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallée de la Clarée |
E925225
|
entity |
| Predicate | closestBorder |
P144886
|
FINISHED |
| Object | Italy |
—
|
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: Italy | Statement: [Vallée de la Clarée, closestBorder, Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestBorder Context triple: [Vallée de la Clarée, closestBorder, Italy]
-
A.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
B.
nearBorderDirection
Indicates that one entity is located close to a border or boundary in a specified directional orientation relative to that border.
-
C.
nearStateBorderWith
chosen
Indicates that one entity is located close to the state border shared with another specified state or region.
-
D.
closestTo
Indicates that one entity is nearer in distance to a reference entity than any other comparable entity.
-
E.
distanceToBorder
Indicates the measured or estimated spatial separation between a given entity or location and the nearest relevant border or boundary.
- 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_69f76eaeb69c8190b367df9330d6f6af |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 3, 2026, 4:32 p.m.