Triple
T25201463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanji Tatsumi |
E631134
|
entity |
| Predicate | shadowRepresents |
P158025
|
FINISHED |
| Object | repressed insecurities about masculinity |
—
|
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: repressed insecurities about masculinity | Statement: [Kanji Tatsumi, shadowRepresents, repressed insecurities about masculinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shadowRepresents Context triple: [Kanji Tatsumi, shadowRepresents, repressed insecurities about masculinity]
-
A.
cornerRepresents
Indicates that a particular corner in a structure, diagram, or space stands for or symbolizes another element, concept, or feature.
-
B.
isRepresentiveOf
Indicates that one entity serves as an official agent, spokesperson, or proxy acting on behalf of another entity.
-
C.
rimRepresents
Indicates that one entity serves as a representation, model, or stand-in for another entity within a specific context or system.
-
D.
representationIn
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
-
E.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
- 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_69e75a8b86c4819089eda22c843b739f |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f474b5e4408190b726bbd038fa3862 |
completed | May 1, 2026, 9:39 a.m. |
| PD | Predicate disambiguation | batch_69f44d849e7c81909945438f40e35362 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 21, 2026, 12:51 p.m.