Triple
T3280002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cupid |
E68848
|
entity |
| Predicate | symbolicTheme |
P15592
|
FINISHED |
| Object | love is blind |
—
|
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: love is blind | Statement: [Cupid, symbolicTheme, love is blind]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolicTheme Context triple: [Cupid, symbolicTheme, love is blind]
-
A.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
B.
signatureTheme
chosen
Indicates that something serves as a distinctive, defining theme strongly associated with a particular entity or context.
-
C.
symbolicStyle
Indicates that one entity employs or is characterized by a particular symbolic or emblematic style defined by the other entity.
-
D.
themedAs
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
-
E.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
- 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_69ad859c463481909ca4be267336c290 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0166c8c81909cb0a580ef319be3 |
completed | March 8, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.