Triple
T26186877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man in Black |
E654852
|
entity |
| Predicate | wornColorSymbolizes |
P38168
|
FINISHED |
| Object | mourning for the poor and oppressed |
—
|
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: mourning for the poor and oppressed | Statement: [The Man in Black, wornColorSymbolizes, mourning for the poor and oppressed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wornColorSymbolizes Context triple: [The Man in Black, wornColorSymbolizes, mourning for the poor and oppressed]
-
A.
clothingSymbolism
chosen
Indicates how clothing or attire conveys symbolic meaning, such as status, identity, emotion, or cultural significance, within a given context.
-
B.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
C.
wearsColorFrequently
Indicates that an entity regularly and habitually wears items of a particular color.
-
D.
oftenDepictedWearing
Indicates that an entity is frequently shown or represented as wearing a particular item or type of clothing in depictions or portrayals.
-
E.
wornAs
Indicates that one entity is used or put on as clothing, an accessory, or a wearable item by another entity.
- 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_69ee5b469bc081908fe486453fdad810 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60c9df1ac8190a31d3a3fea0b2e16 |
completed | May 2, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69f5b007ec1c819092e2c3605933f60b |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:42 p.m.