Triple
T7171805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Kistiakowsky |
E167216
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Emma |
E30843
|
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: Emma | Statement: [Emma Kistiakowsky, givenName, Emma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Context triple: [Emma Kistiakowsky, givenName, Emma]
-
A.
Emma
chosen
Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
-
B.
Emma
"Emma" is a 2009 British television miniseries adaptation of Jane Austen's novel, starring Romola Garai in the title role.
-
C.
Emily
Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
-
D.
Emily
Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
-
E.
Emily
"Emily" is a 2022 British biographical drama film about the life of writer Emily Brontë, starring Fionn Whitehead alongside Emma Mackey.
- 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_69c68889a2748190a316c5e65360361a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e88b0a448190a19bd2d9e2a310a4 |
completed | March 27, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b918a838819088bd24d462101902 |
completed | March 28, 2026, 11:18 a.m. |
Created at: March 27, 2026, 2:48 p.m.