Triple
T12857163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Nachtwey |
E307486
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | James Nachtwey |
E307486
|
NE 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: James Nachtwey | Statement: [James Nachtwey, name, James Nachtwey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Nachtwey Context triple: [James Nachtwey, name, James Nachtwey]
-
A.
James Nachtwey
chosen
James Nachtwey is an acclaimed American photojournalist renowned for his powerful war and conflict photography documenting human suffering around the world.
-
B.
Dahr Jamail
Dahr Jamail is an American independent journalist and author best known for his unembedded reporting from Iraq and his critical coverage of U.S. foreign policy and environmental issues.
-
C.
Philip Jones Griffiths
Philip Jones Griffiths was a renowned Welsh photojournalist best known for his powerful and critical coverage of the Vietnam War.
-
D.
Don McCullin
Don McCullin is a renowned British photojournalist celebrated for his powerful and often harrowing images of war, conflict, and social hardship around the world.
-
E.
Michael Wolf
Michael Wolf is an actor known for his role in the television series "Embassy."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970231ce48190a4eabc4b8c24a3ff |
completed | April 10, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69ba9a53c81908e9ed120f6cb94af |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:37 p.m.