Triple
T4724678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John W. Henry |
E104852
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Mai Henry |
E104852
|
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: Mai Henry | Statement: [John W. Henry, spouse, Mai Henry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mai Henry Context triple: [John W. Henry, spouse, Mai Henry]
-
A.
Mai Henry
chosen
Mai Henry is the former wife of American businessman and sports team owner John W. Henry.
-
B.
Hannah Sullivan
Hannah Sullivan is a contemporary British poet and academic whose debut collection "Three Poems" won widespread acclaim for its innovative, formally adventurous exploration of modern life.
-
C.
Mai
Mai is the traditional royal title used for rulers in Kanuri society, historically associated with the kings of the Kanem-Bornu Empire in the Lake Chad region.
-
D.
Sophia Young
Sophia Young is a retired WNBA forward best known as a multi-time All-Star and franchise cornerstone of the San Antonio Silver Stars.
-
E.
Mia Dolan
Mia Dolan is an aspiring actress in Los Angeles and one of the two central protagonists of the musical film "La La Land."
- 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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64456a6c8190b658216b62ef82cf |
completed | March 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be10986d688190ad82e7f959c50434 |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:18 p.m.