Triple
T8509660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armory Show |
E201418
|
entity |
| Predicate | numberOfWorksExhibited |
P5288
|
FINISHED |
| Object | approximately 1300 |
—
|
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: approximately 1300 | Statement: [Armory Show, numberOfWorksExhibited, approximately 1300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorksExhibited Context triple: [Armory Show, numberOfWorksExhibited, approximately 1300]
-
A.
numberOfExhibits
chosen
Indicates the total count of exhibits associated with a given entity or context.
-
B.
exhibitsWorkOf
Indicates that one entity displays or presents the creative works produced by another entity.
-
C.
hasExhibitionsAbout
Indicates that one entity organizes or presents exhibitions whose subject matter concerns another entity.
-
D.
exhibitedWith
Indicates that two or more entities were presented or displayed together as part of the same exhibition or show.
-
E.
exhibitedAs
Indicates that something is presented or displayed in a particular context, such as in a show, gallery, or exhibition.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5e0cb1881909d1ff6ee9b3a65cc |
completed | March 31, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:15 p.m.