Triple
T33739446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edina Monsoon |
E864518
|
entity |
| Predicate | hasBodyImageConcern |
P100754
|
FINISHED |
| Object | weight |
—
|
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: weight | Statement: [Edina Monsoon, hasBodyImageConcern, weight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyImageConcern Context triple: [Edina Monsoon, hasBodyImageConcern, weight]
-
A.
hasBodyImageIssue
chosen
Indicates that an entity experiences concerns, dissatisfaction, or negative perceptions about their own body or physical appearance.
-
B.
hasGivingBodyType
Indicates that one entity serves as the physical or organizational source that gives or grants something to another entity.
-
C.
hasBodyComposition
Indicates a relationship where an entity possesses or is characterized by a particular makeup or proportion of physical components (such as tissues, substances, or materials) in its body.
-
D.
hasFacialSkinColor
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
-
E.
hasBareFacialSkin
Indicates that an entity’s facial area is uncovered or not obscured by hair, clothing, or other materials.
- 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_69f3498b24b8819096a65009e521d0e1 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd64bc86848190a49f451a8fc5cf1e |
completed | May 8, 2026, 4:21 a.m. |
| PD | Predicate disambiguation | batch_69fd5ff4a648819090756d90fd195d9a |
completed | May 8, 2026, 4 a.m. |
Created at: May 1, 2026, 1:44 a.m.