Triple
T2819316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Easter Alleluia |
E54368
|
entity |
| Predicate | languageElement |
P7161
|
FINISHED |
| Object | Alleluia |
—
|
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: Alleluia | Statement: [Easter Alleluia, languageElement, Alleluia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageElement Context triple: [Easter Alleluia, languageElement, Alleluia]
-
A.
hasLinguisticElement
chosen
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
-
B.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
E.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abdf15b7288190a03d1193cc0544a6 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd08f2f481908c3da8a9c7a00552 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.