Triple
T13983285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Woman I Kept to Myself |
E336367
|
entity |
| Predicate | relatedWorkByAuthor |
P922
|
FINISHED |
| Object | Yo! |
E336360
|
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: Yo! | Statement: [The Woman I Kept to Myself, relatedWorkByAuthor, Yo!]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yo! Context triple: [The Woman I Kept to Myself, relatedWorkByAuthor, Yo!]
-
A.
Yo!
chosen
"Yo!" is a novel by Dominican-American author Julia Alvarez that explores identity, storytelling, and cultural displacement through the fragmented perspectives of people surrounding a writer nicknamed Yo.
-
B.
The Yo
The Yo is a colloquial nickname for Youngstown, Ohio, often used by locals to refer to the city in a familiar, informal way.
-
C.
Yo Yo
"Yo Yo" is a song featured on the soundtrack album for the film "Car Wash."
-
D.
Yo Yo Yo
"Yo Yo Yo" is a track featured on the indie rock compilation album "Take 'Em to the Cleaners" by the band The Cleaners from Venus.
-
E.
Yo-Yo
Yo-Yo is an American rapper and actress known for her socially conscious lyrics and prominent role in early 1990s West Coast hip hop.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea2e8808190a1203a6386224bd8 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac942ba481908858d7f214085b5f |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:18 p.m.