Triple
T279924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject |
E5329
|
entity | |
| Predicate | supportsContentFormat |
P203
|
FINISHED |
| Object | images |
—
|
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: images | Statement: [Instagram, supportsContentFormat, images]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsContentFormat Context triple: [Instagram, supportsContentFormat, images]
-
A.
supportsFeature
chosen
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
B.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
C.
hasSupported
Indicates that one entity has provided assistance, endorsement, or backing to another entity, either materially, emotionally, or through advocacy.
-
D.
supportsBody
Indicates that one entity physically or structurally holds up, bears the weight of, or provides foundational stability for another entity’s body.
-
E.
supportsProjectType
Indicates that one entity is capable of handling, accommodating, or being compatible with a specified type of project.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25def95c48190bb8ab2259f67b583 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b765f488190b2cbe4b45cd42821 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.