Triple
T36518582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champaubert-aux-Bois |
E900114
|
entity |
| Predicate | hasCurrentUseOfArea |
P196805
|
FINISHED |
| Object | artificial lake |
—
|
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: artificial lake | Statement: [Champaubert-aux-Bois, hasCurrentUseOfArea, artificial lake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCurrentUseOfArea Context triple: [Champaubert-aux-Bois, hasCurrentUseOfArea, artificial lake]
-
A.
hasDayUseArea
Indicates that a location or facility includes an area designated for daytime, non-overnight public use.
-
B.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
hasCentralAreaUse
Indicates that an entity’s central area is used or designated for a particular function or purpose.
-
D.
hasSurfaceUse
Indicates that something is used or intended to be used on a surface (e.g., applied to, covering, or interacting with a surface).
-
E.
hasAreaOfCoverage
Indicates that an entity provides services, influence, or applicability within a specified geographic or conceptual region.
- 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_69f76e5dada881909da2d34bc7a9202a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
| PDg | Predicate description generation | batch_69fe68a385f48190b942700e3eddc9b6 |
completed | May 8, 2026, 10:50 p.m. |
Created at: May 3, 2026, 4:11 p.m.