Triple
T213070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eid al-Fitr |
E4757
|
entity |
| Predicate | fastingRelation |
P37
|
FINISHED |
| Object | celebrates completion of obligatory Ramadan fast |
—
|
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: celebrates completion of obligatory Ramadan fast | Statement: [Eid al-Fitr, fastingRelation, celebrates completion of obligatory Ramadan fast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fastingRelation Context triple: [Eid al-Fitr, fastingRelation, celebrates completion of obligatory Ramadan fast]
-
A.
preparatoryFastBegins
Indicates that a required period of fasting starts in preparation for a subsequent event, action, or ritual.
-
B.
temporalRelation
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
C.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
E.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c313d108190a65d3e939f961bef |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b509400819093a6c1a1bac861e3 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.