Triple
T1282457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dick Costolo |
E27356
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dick Costolo |
E27356
|
NE 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: Dick Costolo | Statement: [Dick Costolo, name, Dick Costolo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dick Costolo Context triple: [Dick Costolo, name, Dick Costolo]
-
A.
Dick Costolo
chosen
Dick Costolo is an American entrepreneur and former stand-up comedian best known for serving as CEO of Twitter during its rapid growth and public offering in the early 2010s.
-
B.
Marc Benioff
Marc Benioff is an American billionaire entrepreneur and philanthropist best known as the co-founder, chairman, and CEO of cloud software company Salesforce.
-
C.
John Donahoe
John Donahoe is an American business executive best known as the CEO of Nike, Inc. and former CEO of eBay and ServiceNow.
-
D.
Reid Hoffman
Reid Hoffman is an American entrepreneur, venture capitalist, and co-founder of LinkedIn, known for his influential role in the tech industry and philanthropy.
-
E.
Biz Stone
Biz Stone is an American entrepreneur and software developer best known as one of the co-founders of Twitter and a prominent figure in the social media industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b47be08190828a1c0a11d94ce8 |
completed | March 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2fdb3ac81909bc836e2a655130c |
completed | March 7, 2026, 10:13 p.m. |
Created at: March 1, 2026, 7:50 p.m.