Triple
T14279760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hippolytus (Euripides) |
E354011
|
entity |
| Predicate | trilogyContext |
P24632
|
FINISHED |
| Object | presented with other plays at the City Dionysia |
—
|
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: presented with other plays at the City Dionysia | Statement: [Hippolytus (Euripides), trilogyContext, presented with other plays at the City Dionysia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trilogyContext Context triple: [Hippolytus (Euripides), trilogyContext, presented with other plays at the City Dionysia]
-
A.
trilogyTheme
Indicates that multiple works in a trilogy share a common overarching theme or central subject.
-
B.
partOfTrilogy
chosen
Indicates that one work belongs to a set of three related works that together form a trilogy.
-
C.
novelTrilogyTitle
Indicates that a given title is the name of a trilogy of novels.
-
D.
contextOf
Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
-
E.
hasSequelInTrilogy
Indicates that one work in a trilogy is followed by another work that serves as its sequel within that same three-part series.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6585270c8190a717127b2f5dab3b |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.