Triple
T5808607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suresnes American Cemetery |
E128809
|
entity |
| Predicate | hasChapelDecorationStyle |
P57617
|
FINISHED |
| Object | classical |
—
|
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: classical | Statement: [Suresnes American Cemetery, hasChapelDecorationStyle, classical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelDecorationStyle Context triple: [Suresnes American Cemetery, hasChapelDecorationStyle, classical]
-
A.
hasChapelDecoration
Indicates that a chapel possesses or features a particular decorative element or ornamentation.
-
B.
hasChapelStyle
chosen
Indicates that a chapel possesses or is characterized by a particular architectural or stylistic design.
-
C.
hasCathedralStyle
Indicates that something possesses or is characterized by a particular architectural style associated with a cathedral.
-
D.
hasChapelCountApprox
Indicates an approximate number of chapels associated with an entity.
-
E.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1867a481909a7ea3331dbb04ce |
completed | March 22, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69c021d5ecd081908a62dd66e26f8598 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:52 p.m.