Triple
T1065323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebekah |
E22996
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Becca |
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: Becca | Statement: [Rebekah, hasShortForm, Becca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Becca Context triple: [Rebekah, hasShortForm, Becca]
-
A.
Becky
chosen
Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
-
B.
Rebeca
Rebeca is a feminine given name, commonly used in Spanish- and Portuguese-speaking countries, that is a variant of the name Rebecca.
-
C.
Hadley Beeman
Hadley Beeman is a web standards and technology governance expert known for her leadership within the World Wide Web Consortium (W3C) and related digital policy initiatives.
-
D.
Brenna
Brenna is a Norwegian surname most notably borne by Tonje Brenna, a contemporary Norwegian politician.
-
E.
Chloe
Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b90f91248190ace1534a51b82bdd |
completed | March 1, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e5bc6348190a0d23fe269707e1b |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 7:42 p.m.