Triple
T35256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin Mary |
E698
|
entity |
| Predicate | centralThemeIn |
P1183
|
FINISHED |
| Object | Marian devotions |
—
|
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: Marian devotions | Statement: [Virgin Mary, centralThemeIn, Marian devotions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralThemeIn Context triple: [Virgin Mary, centralThemeIn, Marian devotions]
-
A.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
B.
coreIdea
Indicates the central concept or primary message that underlies or unifies something, such as a text, argument, or work.
-
C.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
D.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
E.
hasCentralFigure
chosen
Indicates that something features a primary or most important figure at its core or focus.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24989c3308190af59dfae37cfc32f |
completed | Feb. 28, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69a24873e97c8190b9e4279e43b6de14 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.