Triple
T22028394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timeline panel |
E544022
|
entity |
| Predicate | representsDataAs |
P21655
|
FINISHED |
| Object | timeline graphs |
—
|
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: timeline graphs | Statement: [Timeline panel, representsDataAs, timeline graphs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsDataAs Context triple: [Timeline panel, representsDataAs, timeline graphs]
-
A.
representsAs
Indicates that one entity serves as a depiction, symbol, or stand-in for another entity in some representational context.
-
B.
canRepresent
Indicates that one entity is capable of serving as a valid stand-in, proxy, or expression for another entity in a given context.
-
C.
representationIn
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
-
D.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
E.
representationType
chosen
Indicates the specific form or mode in which something is represented or expressed (e.g., as a symbol, image, model, or description).
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127cdf5c08190ac804664d6e56fe2 |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:24 p.m.