Triple
T28723624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zahara Collection |
E730161
|
entity |
| Predicate | hasValueFocus |
P165265
|
FINISHED |
| Object | ethical sourcing |
—
|
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: ethical sourcing | Statement: [Zahara Collection, hasValueFocus, ethical sourcing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasValueFocus Context triple: [Zahara Collection, hasValueFocus, ethical sourcing]
-
A.
hasVisualFocus
Indicates that one entity is currently directing its visual attention or gaze toward another entity.
-
B.
hasValue
Indicates that an entity is associated with a specific numerical, textual, or otherwise defined value.
-
C.
hasFocusText
Indicates that one entity provides the primary or highlighted textual content associated with another entity.
-
D.
hasCharacterFocus
Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
-
E.
hasRDFocus
Indicates that something has a specific region of interest or focal area within an image, scene, or dataset that is being emphasized or analyzed.
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6570be4748190902852f5fa92cf54 |
completed | May 2, 2026, 7:57 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 5:54 a.m.