Triple
T146721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twitter, Inc. |
E3345
|
entity |
| Predicate | majorRevenueSource |
P7220
|
FINISHED |
| Object | digital advertising |
—
|
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: digital advertising | Statement: [Twitter, Inc., majorRevenueSource, digital advertising]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorRevenueSource Context triple: [Twitter, Inc., majorRevenueSource, digital advertising]
-
A.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
B.
majorExport
Indicates that something is a primary or significant export product or resource of a given entity (such as a country or region).
-
C.
majorCustomer
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
-
D.
majorStudio
Indicates that an entity is a large, primary film or media production and distribution company within the entertainment industry.
-
E.
capital
Indicates that one place serves as the official seat of government or primary administrative center for another political entity.
- 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_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2587e598c81909e1082b813971f48 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.