Triple
T5026000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sicily-Rome American Cemetery |
E112975
|
entity |
| Predicate | hasChapelDecoration |
P60590
|
FINISHED |
| Object | mosaics |
—
|
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: mosaics | Statement: [Sicily-Rome American Cemetery, hasChapelDecoration, mosaics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelDecoration Context triple: [Sicily-Rome American Cemetery, hasChapelDecoration, mosaics]
-
A.
hasChapelStyle
Indicates that a chapel possesses or is characterized by a particular architectural or stylistic design.
-
B.
hasChapelCountApprox
Indicates an approximate number of chapels associated with an entity.
-
C.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
D.
hasChapelArchitect
Indicates that an entity has another entity serving as the architect responsible for designing its chapel.
-
E.
hasChapelRequirement
Indicates that an entity is subject to a requirement to attend or participate in chapel or religious services.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd738c3aac81908fb6a5c70c97a394 |
completed | March 20, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd724ff2b4819091351cf80d3647a1 |
completed | March 20, 2026, 4:14 p.m. |
Created at: March 20, 2026, 1:36 p.m.