Triple
T27990395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pearblossom Hwy., 11–18th April 1986, #2 |
E706853
|
entity |
| Predicate | number of images (approximate) |
P130124
|
FINISHED |
| Object | over 700 photographs |
—
|
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 700 photographs | Statement: [Pearblossom Hwy., 11–18th April 1986, #2, number of images (approximate), over 700 photographs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: number of images (approximate) Context triple: [Pearblossom Hwy., 11–18th April 1986, #2, number of images (approximate), over 700 photographs]
-
A.
hasApproximateNumberOfImages
chosen
Indicates that an entity is associated with a quantity of images that is approximate rather than an exact count.
-
B.
numberOfImagesReturned
Indicates the total count of images that are produced or provided as the result of a query, request, or operation.
-
C.
numberOfStills
Indicates the quantity of still images associated with or contained in a given entity or context.
-
D.
numberOfImagesTaken
Indicates the quantity of images that have been captured or recorded in relation to a given subject or event.
-
E.
workNumberInImagesII
Indicates that a specific work or item is assigned a particular identifying number within a set of images (version II of this numbering relationship).
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
Created at: April 27, 2026, 7:49 p.m.