Triple
T17749113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raise the Red Lantern |
E443066
|
entity |
| Predicate | symbolismOfRedLanterns |
P128639
|
FINISHED |
| Object | favor and power of the master |
—
|
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: favor and power of the master | Statement: [Raise the Red Lantern, symbolismOfRedLanterns, favor and power of the master]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolismOfRedLanterns Context triple: [Raise the Red Lantern, symbolismOfRedLanterns, favor and power of the master]
-
A.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
-
B.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
C.
blackStripeSymbolism
Indicates the symbolic meaning or thematic significance associated with a black stripe in a given context.
-
D.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
E.
hasLanternShape
Indicates that one entity has the form, outline, or configuration characteristic of a lantern.
- F. None of above. chosen
Provenance (4 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48418c0188190beb31809b40e4648 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:10 a.m.