Triple
T3117591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cana |
E65098
|
entity |
| Predicate | numberOfMiraclesTraditionallyAssociated |
P45450
|
FINISHED |
| Object | at least two |
—
|
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: at least two | Statement: [Cana, numberOfMiraclesTraditionallyAssociated, at least two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMiraclesTraditionallyAssociated Context triple: [Cana, numberOfMiraclesTraditionallyAssociated, at least two]
-
A.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
B.
numberOfGreatFeasts
Indicates the total count of great feasts associated with or observed by an entity.
-
C.
numberOfCommandments
Indicates the total count of commandments associated with a given subject.
-
D.
associatedDevotion
Indicates a relationship where one entity is linked to or characterized by a particular devotion, dedication, or religious/spiritual practice connected to another entity.
-
E.
hasNumberOfDeities
Indicates the specific count of deities associated with an entity, such as a religion, mythology, or belief system.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4e73cc88190846ef37ccf1a0de7 |
completed | March 8, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_69ad9df455088190940ad04419772dc8 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:04 p.m.