Triple
T4845817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becky Hammon |
E108287
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Becky |
E38129
|
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: Becky | Statement: [Becky Hammon, nickname, Becky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Becky Context triple: [Becky Hammon, nickname, Becky]
-
A.
Becky
chosen
Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
-
B.
Becca
Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
-
C.
Becky Gates
Becky Gates is the wife of former U.S. Secretary of Defense Robert M. Gates and a longtime partner in his public and academic life.
-
D.
Becky Leeman
Becky Leeman is the ambitious, manipulative beauty pageant contestant and primary antagonist in the dark comedy film "Drop Dead Gorgeous."
-
E.
Becky Johnston
Becky Johnston is an American screenwriter best known for her work on films such as "Seven Years in Tibet" and "The Prince of Tides."
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d19784c81908e256ea23889192b |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cd6dbcc8190b802eeb6d74fd37d |
completed | March 21, 2026, 8:54 a.m. |
Created at: March 20, 2026, 1:25 p.m.