Triple
T4867699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallelujah |
E109010
|
entity |
| Predicate | isWidelyCovered |
P37383
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hallelujah, isWidelyCovered, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWidelyCovered Context triple: [Hallelujah, isWidelyCovered, true]
-
A.
isFrequentlyCovered
chosen
Indicates that an entity is regularly or commonly reported on, discussed, or featured, especially in media or informational sources.
-
B.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
C.
isWidelyUsed
Indicates that something is commonly or extensively utilized across many contexts, users, or situations.
-
D.
hasMediaCoverageSince
Indicates that an entity has had media coverage starting from a specified point in time and continuing from then onward.
-
E.
hasEnduringPopularityOn
Indicates that something continues to be widely liked, used, or appreciated on a particular platform, medium, or context over an extended period of time.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d7bb0b88190bbc24498619910fc |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.