Triple
T30787368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mass of the Immaculate Conception |
E783990
|
entity |
| Predicate | hasProper |
P201621
|
FINISHED |
| Object | Collect prayer for the Immaculate Conception |
—
|
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: Collect prayer for the Immaculate Conception | Statement: [Mass of the Immaculate Conception, hasProper, Collect prayer for the Immaculate Conception]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProper Context triple: [Mass of the Immaculate Conception, hasProper, Collect prayer for the Immaculate Conception]
-
A.
hasProperName
Indicates that an entity is associated with a specific proper name used to uniquely identify it.
-
B.
hasGood
Indicates that one entity possesses or exhibits a positive, beneficial, or desirable quality, condition, or attribute in relation to another.
-
C.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
D.
hasProportion
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
-
E.
hasFair
Indicates that an entity organizes, hosts, or is associated with a fair or similar event.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a000efe971081909de03f875a7ad6cc |
completed | May 10, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a000c4ffe788190a5757af60aadd9f3 |
completed | May 10, 2026, 4:40 a.m. |
| PDg | Predicate description generation | batch_6a000efdbe948190b4bfa9871aa1a7ee |
completed | May 10, 2026, 4:52 a.m. |
Created at: April 29, 2026, 8:41 p.m.