Triple
T32818632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (Washington Metro) stations |
E839370
|
entity |
| Predicate | haveArt |
P164162
|
FINISHED |
| Object | public art installations (selected stations) |
—
|
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: public art installations (selected stations) | Statement: [Red Line (Washington Metro) stations, haveArt, public art installations (selected stations)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveArt Context triple: [Red Line (Washington Metro) stations, haveArt, public art installations (selected stations)]
-
A.
hasArtFeature
Indicates that an entity possesses or is characterized by a particular artistic attribute, element, or stylistic feature.
-
B.
hasArtSubjects
Indicates that an entity is associated with one or more subjects or themes within the domain of art.
-
C.
hasArtCollection
Indicates that an entity possesses, maintains, or is associated with a collection of artworks.
-
D.
artIncludes
Indicates that a work of art contains, incorporates, or is composed of another artistic element or component.
-
E.
hasArtisticWorks
chosen
Indicates that an entity possesses, is associated with, or is the creator of one or more artistic works.
- 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:15 a.m.