Triple
T1309132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Saint Anne in Jerusalem |
E27947
|
entity |
| Predicate | hasApse |
P27818
|
FINISHED |
| Object | triple apse |
—
|
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: triple apse | Statement: [Church of Saint Anne in Jerusalem, hasApse, triple apse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApse Context triple: [Church of Saint Anne in Jerusalem, hasApse, triple apse]
-
A.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
B.
PSE
Indicates a relationship where one entity is engaged in or associated with a public service or public sector employment role relative to another entity or context.
-
C.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
-
D.
hasApp
Indicates that an entity possesses, provides, or is associated with a particular application.
-
E.
hasMP
Indicates that an entity is represented by, or associated with, a specific Member of Parliament (MP).
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c15490a88190872c3d2698a8f9c9 |
completed | March 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69a4bee9e4a88190b22ab2ee831a23c9 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c15361c8819094b8171e780b5560 |
completed | March 1, 2026, 10:44 p.m. |
Created at: March 1, 2026, 7:51 p.m.