Triple
T11299000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noelle Quinn |
E267527
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Noelle |
E569144
|
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: Noelle | Statement: [Noelle Quinn, givenName, Noelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noelle Context triple: [Noelle Quinn, givenName, Noelle]
-
A.
Noelle
chosen
Noelle is a Christmas-themed comedy film starring Anna Kendrick as Santa Claus’s daughter who must save the family business when her brother goes missing.
-
B.
Noelle Quinn
Noelle Quinn is a former standout UCLA Bruins guard who became a WNBA player and later head coach of the Seattle Storm.
-
C.
Noellie
Noellie is a feminine given name, used here as part of the full name Amélie Noellie Parayre.
-
D.
Annelise
Annelise is the given name of Anni Albers, the influential German-born textile artist and printmaker associated with the Bauhaus and later American modernism.
-
E.
Chloe
Chloe is a 2009 psychological thriller film directed by Atom Egoyan, known for its themes of infidelity and obsession and starring Amanda Seyfried, Julianne Moore, and Liam Neeson.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a3616c8190a8fd23ca67463806 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a3e26e88190991127a5993a32a4 |
completed | April 19, 2026, 5 p.m. |
Created at: April 8, 2026, 9:32 p.m.