Triple
T36653329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Théméricourt |
E904922
|
entity |
| Predicate | isScenicCountryside |
P186121
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Théméricourt, isScenicCountryside, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isScenicCountryside Context triple: [Théméricourt, isScenicCountryside, true]
-
A.
isScenicTown
Indicates that a town is visually attractive or picturesque, often due to its natural surroundings, architecture, or overall aesthetic appeal.
-
B.
isScenicVillage
Indicates that a village is characterized by visually attractive, picturesque, or charming surroundings.
-
C.
isScenicArea
Indicates that a location is recognized as a scenic area, typically valued for its natural beauty or visually appealing surroundings.
-
D.
hasRuralLandscapeType
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
-
E.
isPartOfScenicVista
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
- 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 3, 2026, 4:11 p.m.