Triple
T9540137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn, Iowa |
E230130
|
entity |
| Predicate | hasFlagDisplayTheme |
P61999
|
FINISHED |
| Object | United States flags |
—
|
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: United States flags | Statement: [Brooklyn, Iowa, hasFlagDisplayTheme, United States flags]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlagDisplayTheme Context triple: [Brooklyn, Iowa, hasFlagDisplayTheme, United States flags]
-
A.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
B.
hasThemingDetail
chosen
Indicates that something includes or is associated with a specific thematic element, motif, or stylistic detail.
-
C.
supportsThemingSystem
Indicates that an entity is compatible with and can operate using a theming system for customizable appearance or style.
-
D.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
E.
usesThemeFrom
Indicates that one work incorporates, references, or is based on the thematic material of another work.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e695948190ab107fff38c57de7 |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.