Triple
T9233374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argos Limited |
E221875
|
entity |
| Predicate | stockKeepingUnitFocus |
P87710
|
FINISHED |
| Object | multi-category retailer |
—
|
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: multi-category retailer | Statement: [Argos Limited, stockKeepingUnitFocus, multi-category retailer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stockKeepingUnitFocus Context triple: [Argos Limited, stockKeepingUnitFocus, multi-category retailer]
-
A.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
C.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
D.
categoryFocus
Indicates that one entity is the primary subject, theme, or focal point within the broader category defined by the other entity.
-
E.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccee1baa3c8190870d1e850ccab1e0 |
completed | April 1, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:29 p.m.