Triple
T15217864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modified National Institute of Standards and Technology database |
E363685
|
entity |
| Predicate | totalNumberOfImages |
P59620
|
FINISHED |
| Object | 70000 |
—
|
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: 70000 | Statement: [Modified National Institute of Standards and Technology database, totalNumberOfImages, 70000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalNumberOfImages Context triple: [Modified National Institute of Standards and Technology database, totalNumberOfImages, 70000]
-
A.
numberOfImagesReturned
chosen
Indicates the total count of images that are produced or provided as the result of a query, request, or operation.
-
B.
numberOfImagesTaken
Indicates the quantity of images that have been captured or recorded in relation to a given subject or event.
-
C.
numberOfStills
Indicates the quantity of still images associated with or contained in a given entity or context.
-
D.
hasNumberOfStills
Indicates that an entity is associated with a specific count of still images or frames.
-
E.
numberOfIllustrations
Indicates the quantity of illustrations associated with or contained in an 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.