Triple
T151988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life |
E3450
|
entity |
| Predicate | positionInIndustry |
P5598
|
FINISHED |
| Object | leading American photojournalism magazine of the 20th century |
—
|
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: leading American photojournalism magazine of the 20th century | Statement: [Life, positionInIndustry, leading American photojournalism magazine of the 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInIndustry Context triple: [Life, positionInIndustry, leading American photojournalism magazine of the 20th century]
-
A.
sponsorOccupation
Indicates that one entity serves as the occupation or professional role of a sponsor associated with another entity.
-
B.
subjectPosition
Indicates the spatial or logical position of a subject relative to a reference frame, context, or other entities.
-
C.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- F. None of above. chosen
Provenance (4 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580f55a88190b37b54ee0ed5ac7c |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565adaf48190b68ae4444ff83ccd |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256eb46ec81909c730000e5041d0d |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.