Triple
T363215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nike, Inc. |
E7899
|
entity |
| Predicate | revenueRank |
P1944
|
FINISHED |
| Object | one of the world’s largest athletic apparel companies |
—
|
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: one of the world’s largest athletic apparel companies | Statement: [Nike, Inc., revenueRank, one of the world’s largest athletic apparel companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revenueRank Context triple: [Nike, Inc., revenueRank, one of the world’s largest athletic apparel companies]
-
A.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
B.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
C.
majorRevenueSource
Indicates that one entity serves as the primary or dominant source of revenue for another entity.
-
D.
rankedBy
Indicates that one entity is ordered or assigned a position in a hierarchy or list according to criteria determined or applied by another entity.
-
E.
rankedAs
chosen
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
- F. None of above.
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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebd1016481909b8ba3b047a47145 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95c843c8190b2aba9af6e869ba1 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.