Triple
T27720838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivarais |
E698948
|
entity |
| Predicate | highestArea |
P32773
|
FINISHED |
| Object | Massif Central foothills |
—
|
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: Massif Central foothills | Statement: [Vivarais, highestArea, Massif Central foothills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestArea Context triple: [Vivarais, highestArea, Massif Central foothills]
-
A.
hasLargestAreaOf
chosen
Indicates that the subject entity possesses the greatest area (size of surface or region) compared to the other entities in the specified set or context.
-
B.
hasHighestAreas
Indicates that the subject possesses the largest or most extensive areas compared to other relevant entities or regions.
-
C.
largestNeighborhoodByArea
Indicates the relationship where a neighborhood is identified as the one with the greatest land area among a specified set or within a given region.
-
D.
floorAreaRank
Indicates the relative ordering of entities based on the size of their floor area, with lower ranks representing larger floor areas.
-
E.
hasLargeArea
Indicates that an entity occupies or covers a spatial region whose size exceeds a specified large-area threshold.
- 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_69ef591012dc8190a6f1ec994f9f7ff7 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 3:06 p.m.