Triple
T295183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revolution Money |
E6076
|
entity |
| Predicate | competitivePositioning |
P5254
|
FINISHED |
| Object | competitor to traditional credit card networks |
—
|
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: competitor to traditional credit card networks | Statement: [Revolution Money, competitivePositioning, competitor to traditional credit card networks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competitivePositioning Context triple: [Revolution Money, competitivePositioning, competitor to traditional credit card networks]
-
A.
brandPositioning
chosen
Indicates how a brand is strategically placed and perceived in the minds of its target audience relative to competitors.
-
B.
positioning
Indicates the spatial or contextual arrangement of one entity relative to another or within a given environment.
-
C.
marketPosition
Indicates the relative standing or rank an entity holds within a specific market compared to its competitors.
-
D.
positionInIndustry
Indicates the role, rank, or standing that an entity holds within a particular industry or sector.
-
E.
positionB
Indicates that one entity occupies or is located at a specific position relative to another entity.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e9e273f88190ac5355d1310376ed |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9368894819093eeae4347dfcc5a |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.