Triple
T1491219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chokepoint Capitalism |
E29583
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object | Rebecca Giblin |
E243784
|
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: Rebecca Giblin | Statement: [Chokepoint Capitalism, coAuthor, Rebecca Giblin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebecca Giblin Context triple: [Chokepoint Capitalism, coAuthor, Rebecca Giblin]
-
A.
Rebecca Giblin
chosen
Rebecca Giblin is an Australian legal scholar and advocate specializing in copyright, technology, and creators’ rights, known for her work on how digital platforms affect cultural industries.
-
B.
Beverly Gage
Beverly Gage is an American historian and Yale professor known for her scholarship on 20th-century U.S. political history and her acclaimed biography of FBI director J. Edgar Hoover.
-
C.
Judith Nelson
Judith Nelson was an American soprano known for her pioneering work and acclaimed performances in the early music and Baroque repertoire.
-
D.
Molly Smith
Molly Smith is a daughter of FedEx founder and CEO Frederick W. Smith.
-
E.
Molly Smith
Molly Smith is an American film producer known for her work on acclaimed movies such as the crime thriller "Sicario."
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c3ace4819081bc2b86ee2486b6 |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6adcef5881908cefd7d575b85323 |
completed | March 9, 2026, 6:38 a.m. |
Created at: March 1, 2026, 8:12 p.m.