Triple
T11319370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meg Tilly |
E268050
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Will Firth |
E18169
|
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: Will Firth | Statement: [Meg Tilly, child, Will Firth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Firth Context triple: [Meg Tilly, child, Will Firth]
-
A.
Will Firth
chosen
Will Firth is the son of English actor Colin Firth and is known primarily for his connection to his father's prominent film career.
-
B.
Darren Gilshenan
Darren Gilshenan is an Australian actor and comedian known for his work in television, film, and theatre, particularly in character and comic roles.
-
C.
Rupert Falkner
Rupert Falkner is a fictional protagonist named Falkner who serves as the central figure in the narrative that bears his surname.
-
D.
Aidan Chambers
Aidan Chambers is a British author and critic best known for his innovative and award-winning young adult novels, including the Carnegie Medal–winning "Postcards from No Man’s Land."
-
E.
Charlie Creed-Miles
Charlie Creed-Miles is an English actor known for his gritty roles in British film and television, including prominent performances in crime and drama productions.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9de875481908acfa56015d4b46f |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e525e2549081909ec99e4c7006fd66 |
completed | April 19, 2026, 6:58 p.m. |
Created at: April 8, 2026, 9:32 p.m.