Triple
T4705523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keith Haring |
E104382
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Yoko Ono |
E93289
|
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: Yoko Ono | Statement: [Keith Haring, collaboratedWith, Yoko Ono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoko Ono Context triple: [Keith Haring, collaboratedWith, Yoko Ono]
-
A.
Yoko Ono
chosen
Yoko Ono is a Japanese multimedia artist, musician, and peace activist known for her avant-garde work and her marriage and collaborations with John Lennon.
-
B.
Yoko Satō
Yoko Satō is a Japanese individual known for bearing the surname Satō, which is one of the most common family names in Japan.
-
C.
Yoko
Yoko is a Japanese given name commonly used for women and borne by various notable figures in arts, literature, and entertainment.
-
D.
Joan Jonas
Joan Jonas is an influential American visual artist and pioneer of performance and video art whose experimental, multimedia works have significantly shaped contemporary art since the late 1960s.
-
E.
Yoko Murakami
Yoko Murakami is the wife of acclaimed Japanese novelist Haruki Murakami and has been a close creative and personal partner throughout his literary career.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63e808c88190877e98408498fb62 |
completed | March 20, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03d074348190a19092fa02a0bb39 |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:17 p.m.