Triple
T2435173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transubstantiation |
E52942
|
entity |
| Predicate | latinTerm |
P24083
|
FINISHED |
| Object | transubstantiatio |
—
|
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: transubstantiatio | Statement: [Transubstantiation, latinTerm, transubstantiatio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: latinTerm Context triple: [Transubstantiation, latinTerm, transubstantiatio]
-
A.
languageTerm
chosen
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
B.
romanProvinceOpposite
Indicates that two Roman provinces are located on opposite sides of a defined geographic feature or boundary, such as a sea, river, or frontier line.
-
C.
keyTerm
Indicates that a term functions as a primary or central concept within a given context or information structure.
-
D.
coinedTerm
Indicates that an entity originated and introduced a particular term or expression into use.
-
E.
eraName
Indicates the named historical or chronological era associated with an entity or time period.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
Created at: March 6, 2026, 9:43 p.m.