Triple
T1885677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Κρίτων |
E39957
|
entity |
| Predicate | openingScene |
P31333
|
FINISHED |
| Object | Crito visiting Socrates in prison at dawn |
—
|
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: Crito visiting Socrates in prison at dawn | Statement: [Κρίτων, openingScene, Crito visiting Socrates in prison at dawn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingScene Context triple: [Κρίτων, openingScene, Crito visiting Socrates in prison at dawn]
-
A.
openingSituation
chosen
Indicates the initial state, context, or set of conditions that exist at the beginning of an event, interaction, or narrative.
-
B.
openingInvocation
Indicates the act of formally beginning an event, process, or sequence through an initiating statement, action, or call.
-
C.
initialOpening
Indicates the first or earliest instance in which something is opened, begun, or made accessible.
-
D.
openingLine
Indicates that one entity is the first line or initial statement that begins another entity, such as a text, speech, or conversation.
-
E.
openingTheme
Indicates that one entity serves as the opening theme (such as a song or musical piece) for another entity, typically a show, series, or similar work.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb4f53f408190ae30e1a12721e7d7 |
completed | March 7, 2026, 5:17 a.m. |
| PD | Predicate disambiguation | batch_69abafe497a88190a1da6af2888b71b4 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.