Triple
T721475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chair of Saint Peter |
E14625
|
entity |
| Predicate | locatedInPartOf |
P40
|
FINISHED |
| Object | apse of St. Peter's Basilica |
—
|
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: apse of St. Peter's Basilica | Statement: [Chair of Saint Peter, locatedInPartOf, apse of St. Peter's Basilica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInPartOf Context triple: [Chair of Saint Peter, locatedInPartOf, apse of St. Peter's Basilica]
-
A.
hasPartIn
Indicates that an entity participates in or plays a role within a larger event, process, or composite entity.
-
B.
locatedIn
chosen
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
C.
partlyLocatedOn
Indicates that one entity is situated such that only a portion of it lies on or within the spatial extent of another entity.
-
D.
isNotPartOf
Indicates that one entity does not belong to, is not contained within, and is not a component or member of another entity.
-
E.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58fa41c819082de2cc4e0cb2943 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f513608190b716b939d574c292 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.