Triple
T23388319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dedication of the Archbasilica of Saint John Lateran |
E593943
|
entity |
| Predicate | hasProperOfficeTexts |
P152059
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dedication of the Archbasilica of Saint John Lateran, hasProperOfficeTexts, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProperOfficeTexts Context triple: [Dedication of the Archbasilica of Saint John Lateran, hasProperOfficeTexts, yes]
-
A.
hasProperOffice
Indicates that an entity maintains an officially designated, appropriate office or place of business.
-
B.
hasSupportingOffice
Indicates that an entity is associated with or served by a particular office that provides support or administrative services to it.
-
C.
hasLayOffice
Indicates that an individual holds or has held a non-ordained (lay) official position or role within an organization or institution.
-
D.
hasAssociatedOffice
Indicates that an entity is linked to or connected with a particular office in an official or functional capacity.
-
E.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a499bad88190afca1afb2e3fddb0 |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:35 p.m.