Triple
T30444667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | statue of Saint Francis Xavier |
E774542
|
entity |
| Predicate | hasLanguageOfInscriptionPossible |
P15804
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [statue of Saint Francis Xavier, hasLanguageOfInscriptionPossible, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfInscriptionPossible Context triple: [statue of Saint Francis Xavier, hasLanguageOfInscriptionPossible, Latin]
-
A.
hasArabicInscription
Indicates that an entity bears or contains an inscription written in the Arabic script or language.
-
B.
mayBeInscribedOn
Indicates that one entity is permitted or suitable to be written, engraved, or otherwise inscribed on another entity.
-
C.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
D.
hasTypeOfInscriptions
Indicates that an entity bears or is associated with a specific kind or category of inscriptions.
-
E.
secondaryLanguageOfInscriptions
Indicates that a specified language serves as the secondary language used in the inscriptions associated with a given entity.
- 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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
Created at: April 29, 2026, 8:08 p.m.