Triple
T21860490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smiling Angel of Reims |
E539747
|
entity |
| Predicate | hasSmileType |
P68157
|
FINISHED |
| Object | mysterious smile |
—
|
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: mysterious smile | Statement: [Smiling Angel of Reims, hasSmileType, mysterious smile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSmileType Context triple: [Smiling Angel of Reims, hasSmileType, mysterious smile]
-
A.
hasSignatureSmile
chosen
Indicates that an entity is characterized by a distinctive or recognizable smile that serves as a notable or identifying feature.
-
B.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
C.
hasTypeOfEmotion
Indicates that an entity experiences, expresses, or is associated with a particular kind or category of emotion.
-
D.
hasHumorType
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
E.
hasTypeOfMouth
Indicates that an entity possesses a mouth characterized by a specific type or form.
- 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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d63a22b88190b59b13e7b4788195 |
completed | April 28, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:56 p.m.