Triple
T11379615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Église Saint-Médard |
E269558
|
entity |
| Predicate | hasSquareOrForecourt |
P10828
|
FINISHED |
| Object | parvis in front of church |
—
|
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: parvis in front of church | Statement: [Église Saint-Médard, hasSquareOrForecourt, parvis in front of church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSquareOrForecourt Context triple: [Église Saint-Médard, hasSquareOrForecourt, parvis in front of church]
-
A.
hasCourtyard
chosen
Indicates that one entity includes, features, or is characterized by the presence of a courtyard.
-
B.
hasCourtyardFeature
Indicates that a courtyard possesses or includes a specific feature or characteristic.
-
C.
hasCourtyardArea
Indicates that an entity includes or is associated with a courtyard and specifies the size or extent of that courtyard space.
-
D.
hasTennisCourt
Indicates that one entity possesses, includes, or provides access to a tennis court as part of its facilities or attributes.
-
E.
hasGardenSquare
Indicates that an entity includes, is adjacent to, or is otherwise associated with a garden square.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:34 p.m.