Triple
T2393778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liturgy of Saint Gregory of Nazianzus (Coptic) |
E47600
|
entity |
| Predicate | addressForm |
P4477
|
FINISHED |
| Object | second-person address to Christ |
—
|
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: second-person address to Christ | Statement: [Liturgy of Saint Gregory of Nazianzus (Coptic), addressForm, second-person address to Christ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressForm Context triple: [Liturgy of Saint Gregory of Nazianzus (Coptic), addressForm, second-person address to Christ]
-
A.
addressFormFor
chosen
Indicates the form of address or mode of speaking that one entity should use when referring to or speaking to another entity.
-
B.
address
Indicates that one entity directs spoken or written communication specifically to another entity.
-
C.
addressFormat
Indicates the standardized structure or pattern in which an address’s components are arranged and written.
-
D.
addressType
Indicates the specific kind or category of address associated with an entity (e.g., home, work, billing, or shipping).
-
E.
addresses
Indicates that one entity directs speech, communication, or written correspondence specifically toward another entity.
- 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc876d48881909e4d6f5ebe430012 |
completed | March 7, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69abc5a1b5748190b4cd8989700f4dd2 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.