Triple
T5334766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atys |
E123799
|
entity |
| Predicate | hasPrologue |
P9712
|
FINISHED |
| Object | allegorical prologue praising Louis XIV |
—
|
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: allegorical prologue praising Louis XIV | Statement: [Atys, hasPrologue, allegorical prologue praising Louis XIV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrologue Context triple: [Atys, hasPrologue, allegorical prologue praising Louis XIV]
-
A.
hasPrologueSometimes
Indicates that an entity occasionally or in some instances includes a prologue.
-
B.
includesSpokenPrologue
chosen
Indicates that an entity (such as a work or performance) contains a spoken introductory section delivered before the main content begins.
-
C.
hasProperPreface
Indicates that an entity is accompanied by an appropriate and correctly structured introductory preface.
-
D.
hasPrefaceBy
Indicates that a work includes a preface written by a specified person.
-
E.
hasProseDialogue
Indicates that one entity contains or features spoken or conversational content expressed in prose form involving another 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ae52c08190968a5567b7e6b794 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.