Triple
T26394191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pius XIII (Lenny Belardo) |
E663501
|
entity |
| Predicate | fictionalOfficeLocation |
P48856
|
FINISHED |
| Object | Vatican City |
—
|
NE NERFINISHED |
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: Vatican City | Statement: [Pius XIII (Lenny Belardo), fictionalOfficeLocation, Vatican City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalOfficeLocation Context triple: [Pius XIII (Lenny Belardo), fictionalOfficeLocation, Vatican City]
-
A.
fictionalHeadquartersLocation
Indicates the place where a fictional organization, group, or entity is based or has its main headquarters within a fictional context.
-
B.
placeOfOffice
chosen
Indicates the location where an office or official position is held or based.
-
C.
headquartersOfOffice
Indicates that a particular location serves as the main headquarters for a specified office or organizational unit.
-
D.
fictionalResidence
Indicates that one entity is the place where another entity lives or is based within a fictional or imaginary context.
-
E.
workLocationOfFictionalCharacter
Indicates the place or organization where a fictional character is depicted as working within their narrative context.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 26, 2026, 11:27 p.m.