Triple
T37535503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surveyor 7 |
E933183
|
entity |
| Predicate | imageCount |
P65479
|
FINISHED |
| Object | over 20,000 images |
—
|
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: over 20,000 images | Statement: [Surveyor 7, imageCount, over 20,000 images]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageCount Context triple: [Surveyor 7, imageCount, over 20,000 images]
-
A.
numberOfImagesReturned
Indicates the total count of images that are produced or provided as the result of a query, request, or operation.
-
B.
numberOfImagesTaken
chosen
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.
hasApproximateNumberOfImages
Indicates that an entity is associated with a quantity of images that is approximate rather than an exact count.
-
E.
galleryNumber
Indicates the specific gallery or exhibition space in which an item, such as an artwork or artifact, is located or displayed.
- 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.