Triple
T30071626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parish of Santa Eulália |
E764196
|
entity |
| Predicate | hasLandscapeRegion |
P194753
|
FINISHED |
| Object | Alentejo |
—
|
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: Alentejo | Statement: [Parish of Santa Eulália, hasLandscapeRegion, Alentejo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeRegion Context triple: [Parish of Santa Eulália, hasLandscapeRegion, Alentejo]
-
A.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
hasLandscapeValue
Indicates that something possesses aesthetic, cultural, or ecological value specifically related to its landscape or scenic qualities.
-
C.
hasLandscapeProtection
Indicates that an area or object is subject to legal or formal measures aimed at preserving its landscape or scenic character.
-
D.
hasLandscapeRelation
Indicates a spatial or visual relationship between entities within a landscape, such as positioning, adjacency, or contextual association in the environment.
-
E.
hasLandscapeUse
Indicates that something is used or intended to be used within a landscape or landscaping context.
- F. None of above. chosen
Provenance (4 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_69f2247221388190a13a22c47094a0ef |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd864235b481908738dbb69556bc62 |
completed | May 8, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69fd8373b6bc819091c554f29ee17fec |
completed | May 8, 2026, 6:32 a.m. |
| PDg | Predicate description generation | batch_69fd8640e1d4819081c98f15eeb221ab |
completed | May 8, 2026, 6:44 a.m. |
Created at: April 29, 2026, 7 p.m.