Triple
T28983125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Montana |
E734604
|
entity |
| Predicate | displaysText |
P23550
|
FINISHED |
| Object | MONTANA |
—
|
NE NERFINISHED |
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: MONTANA | Statement: [Flag of Montana, displaysText, MONTANA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: displaysText Context triple: [Flag of Montana, displaysText, MONTANA]
-
A.
displays
chosen
Indicates that one entity visually presents or shows another entity’s content or information.
-
B.
languageDisplays
Indicates that one entity presents, shows, or renders another entity in a particular language or linguistic form.
-
C.
textualAppearance
Indicates how something is presented, formatted, or visually structured in written or printed text.
-
D.
textMode
Indicates that something operates, is displayed, or is processed in a mode where information is handled primarily as text rather than as graphics or other media.
-
E.
displaysFeature
Indicates that one entity presents, shows, or makes visible a particular feature or characteristic of another entity.
- 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 9:12 a.m.