Triple
T13184815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary See |
E313820
|
entity |
| Predicate | hasImageRole |
P108940
|
FINISHED |
| Object | matronly figure on See's Candies packaging |
—
|
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: matronly figure on See's Candies packaging | Statement: [Mary See, hasImageRole, matronly figure on See's Candies packaging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImageRole Context triple: [Mary See, hasImageRole, matronly figure on See's Candies packaging]
-
A.
containsImage
Indicates that one entity includes or embeds an image as part of its content or structure.
-
B.
hasImageType
Indicates that an entity is associated with an image of a particular type or format.
-
C.
usesImageModel
Indicates that one entity employs or relies on an image-based model (such as a computer vision or image generation model) in relation to another entity or task.
-
D.
hasKeyImage
Indicates that one entity is designated as the primary or representative image associated with another entity.
-
E.
hasHiddenImage
Indicates that an entity contains or is associated with an image that is not immediately visible or is intentionally concealed from normal view.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:15 p.m.