Triple
T14962653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leela |
E373099
|
entity |
| Predicate | closeFriend |
P8712
|
FINISHED |
| Object | Amy Wong |
E807863
|
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: Amy Wong | Statement: [Leela, closeFriend, Amy Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amy Wong Context triple: [Leela, closeFriend, Amy Wong]
-
A.
Amy Wong
chosen
Amy Wong is a wealthy, klutzy intern and engineering student from Mars who serves as one of the core characters in the animated sci-fi comedy series Futurama.
-
B.
Yun Lee
Yun Lee is the child of Korean-American actor and martial artist Will Yun Lee.
-
C.
Maggie Wong
Maggie Wong is a character from the comedy film "Balls of Fury," known as a skilled and determined ping-pong player who aids the protagonist in his quest.
-
D.
Michelle Wong
Michelle Wong is an actress known for her voice role in the animated feature film "Abominable."
-
E.
Julia Wong
Julia Wong is a film editor best known for her work on major Hollywood productions, including the superhero movie "X-Men: The Last Stand."
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6d0487c8190b7754af8c5014b37 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bdeec408190893d1db9254da24e |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:40 a.m.