Triple
T22726717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elliott Erwitt |
E562013
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | Magnum Photos |
—
|
NE NERFINISHED |
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: Magnum Photos | Statement: [Elliott Erwitt, memberOf, Magnum Photos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magnum Photos Context triple: [Elliott Erwitt, memberOf, Magnum Photos]
-
A.
Magnum Photos
chosen
Magnum Photos is a renowned international photographic cooperative founded in 1947, known for its influential documentary and photojournalistic work by some of the world’s leading photographers.
-
B.
Magnum
Magnum is an OpenStack service that provides container orchestration engines like Kubernetes and Docker Swarm on OpenStack infrastructure.
-
C.
Magnum
Magnum is a popular global ice cream brand known for its premium chocolate-coated ice cream bars.
-
D.
VII Photo Agency
VII Photo Agency is an internationally renowned photographer-owned collective known for its powerful documentary and conflict photography.
-
E.
Irving Penn
Irving Penn was a renowned American photographer celebrated for his elegant fashion images, still lifes, and portraiture for magazines such as Vogue.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1792a2ee48190bfbdde1a72adfd25 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:20 p.m.