Triple
T4886243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amphitryon |
E109444
|
entity |
| Predicate | themeInLiterature |
P39449
|
FINISHED |
| Object | identity and deception by Zeus |
—
|
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: identity and deception by Zeus | Statement: [Amphitryon, themeInLiterature, identity and deception by Zeus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeInLiterature Context triple: [Amphitryon, themeInLiterature, identity and deception by Zeus]
-
A.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
B.
inLiterature
Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
-
C.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
D.
characterTheme
chosen
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
E.
themeInvolvingCharacter
Indicates that a theme, motif, or abstract concept centrally involves or is significantly shaped by a particular character.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e01872c81909607010c10538ad1 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2be5e881909f6ec9c3bcde49f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.