Triple
T10780861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basilica of Bom Jesus |
E254313
|
entity |
| Predicate | bodyExpositionFrequency |
P88910
|
FINISHED |
| Object | approximately every ten years |
—
|
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: approximately every ten years | Statement: [Basilica of Bom Jesus, bodyExpositionFrequency, approximately every ten years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyExpositionFrequency Context triple: [Basilica of Bom Jesus, bodyExpositionFrequency, approximately every ten years]
-
A.
exhibitionFrequency
chosen
Indicates how often an entity is displayed, presented, or exhibited within a given context or time period.
-
B.
exposureType
Indicates the specific manner or context in which one entity is exposed to another entity, condition, or influence.
-
C.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
D.
exposedDuring
Indicates that something becomes visible, accessible, or subject to influence specifically within a given time period, event, or contextual interval.
-
E.
inspectionFrequency
Indicates how often an entity is examined, checked, or reviewed within a given time period.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c48c488190a2b3162202b74726 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.