Triple
T16636111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joy Wang |
E404208
|
entity |
| Predicate | romanticPartner |
P9994
|
FINISHED |
| Object | Becky |
unclear NED1
|
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: Becky | Statement: [Joy Wang, romanticPartner, Becky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Becky Context triple: [Joy Wang, romanticPartner, Becky]
-
A.
Becky
Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
-
B.
Becky
Becky is a character connected to Endora, likely appearing in the same fictional universe or storyline as her.
-
C.
Becky
Becky is a musical act known for its association with the British rock band Dogstar.
-
D.
Becky
Becky is a character from Thomas More’s seminal political-philosophical work "Utopia," representing one of the figures through which the text explores idealized social and political structures.
-
E.
Becky
Becky is a free-spirited young woman in the film "What's Eating Gilbert Grape" who becomes Gilbert Grape's romantic interest and helps him envision a life beyond his small-town burdens.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e999d48190bff680040dbc883d |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dc28df48190b01c1328df24df60 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.