Triple
T5235221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Thompson |
E118204
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Gaia Wise |
E21488
|
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: Gaia Wise | Statement: [Emma Thompson, child, Gaia Wise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaia Wise Context triple: [Emma Thompson, child, Gaia Wise]
-
A.
Gaia Wise
chosen
Gaia Wise is a British actress and the daughter of acclaimed performers Emma Thompson and Greg Wise.
-
B.
Xeni Jardin
Xeni Jardin is an American journalist, blogger, and media commentator best known as a co-editor of Boing Boing and an advocate for digital rights and press freedom.
-
C.
Amelia Kuttner
Amelia Kuttner is a key character in the neo-noir action-comedy film "The Nice Guys," whose disappearance drives the movie’s central investigation.
-
D.
Paula Gunn Allen
Paula Gunn Allen was a Native American poet, novelist, critic, and scholar whose work powerfully advanced Indigenous feminism and Native American literary studies.
-
E.
Diane Venora
Diane Venora is an American actress known for her intense, versatile performances in film, television, and theater, including prominent roles in works like "Heat" and "Romeo + Juliet."
- 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_69bd4467db0881909b3b0982df32cc8f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b064b6881909f5746f55aa422c6 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe6323708190bfc95f01c65dc234 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:49 p.m.