Triple
T2343864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Val-d'Oise |
E45085
|
entity |
| Predicate | containsLandscapeType |
P7342
|
FINISHED |
| Object | suburban areas |
—
|
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: suburban areas | Statement: [Val-d'Oise, containsLandscapeType, suburban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsLandscapeType Context triple: [Val-d'Oise, containsLandscapeType, suburban areas]
-
A.
hasLandscapeType
chosen
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
D.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcade3c808190ab3803538ccbe620 |
completed | March 7, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69abc59616a8819099711834e6f1ccd6 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.