Triple
T12580752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexi Feely |
E300328
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lexi |
E300328
|
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: Lexi | Statement: [Lexi Feely, givenName, Lexi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lexi Context triple: [Lexi Feely, givenName, Lexi]
-
A.
Lexi
Lexi is a common diminutive or nickname for the given name Alexandra.
-
B.
Lexie Littleton
Lexie Littleton is a fictional journalist and love interest in the 2008 sports comedy film "Leatherheads," set against the backdrop of early professional American football.
-
C.
Lexie Richardson
Lexie Richardson is the seemingly perfect, high-achieving eldest daughter of the Richardson family in Celeste Ng’s novel *Little Fires Everywhere*, whose choices expose the novel’s themes of privilege, race, and moral ambiguity.
-
D.
Lexi Underwood
Lexi Underwood is an American actress best known for her breakout role in the television miniseries "Little Fires Everywhere."
-
E.
Lexi Feely
chosen
Lexi Feely is known as the daughter of former NFL placekicker and sports commentator Jay Feely.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6559ba5108190b85be540a405eec8 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 9, 2026, 5:02 p.m.