Triple
T62816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pentecost |
E1246
|
entity |
| Predicate | hasLiturgicalColor |
P4602
|
FINISHED |
| Object | red |
—
|
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: red | Statement: [Pentecost, hasLiturgicalColor, red]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiturgicalColor Context triple: [Pentecost, hasLiturgicalColor, red]
-
A.
hasLiturgicalBook
Indicates that one entity possesses, uses, or is associated with a specific liturgical book in a religious or worship context.
-
B.
hasClergyOrder
Indicates that an entity is associated with, or belongs to, a specific religious or clerical order.
-
C.
hasRiteOrTradition
Indicates that an entity is associated with, practices, or observes a particular rite, ritual, or tradition.
-
D.
liturgicalTradition
Indicates the specific religious rite or ceremonial tradition according to which a worship service, practice, or community operates.
-
E.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251f74b0881909ad89127b8171277 |
completed | Feb. 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69a24ea242c8819086fe00bf01e6523e |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a251f6786081908eaaed6190695322 |
completed | Feb. 28, 2026, 2:24 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.