Triple
T21367586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikki Alexander |
E526960
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Nikki |
—
|
NE NERFINISHED |
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: Nikki | Statement: [Nikki Alexander, hasGivenName, Nikki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nikki Context triple: [Nikki Alexander, hasGivenName, Nikki]
-
A.
Nikki
Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
-
B.
Nikki
Nikki is the estranged wife of Pat Solitano in the film "Silver Linings Playbook," whose separation from him drives much of the movie’s emotional conflict.
-
C.
Nikki
chosen
Nikki is the commonly used first name of American politician and former U.S. Ambassador to the United Nations Nikki Haley.
-
D.
Nikki
Nikki is the central protagonist of the 1993 coming-of-age sports comedy film "Airborne," known for his laid-back California surfer attitude and exceptional inline skating skills.
-
E.
Nikki
Nikki is the main character of the 1994 platform video game "Pandemonium!", known for her acrobatic abilities and whimsical, magical adventures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51e80808190ba5cb05667af02a9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5bae5eb88190be6d9ff4dc03d52b |
completed | April 26, 2026, 6:38 p.m. |
Created at: April 16, 2026, 5:09 p.m.