Triple
T6627906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrow |
E149849
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Willa Holland |
E523790
|
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: Willa Holland | Statement: [Arrow, starring, Willa Holland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willa Holland Context triple: [Arrow, starring, Willa Holland]
-
A.
Willa Holland
chosen
Willa Holland is an American actress and model best known for her roles on the television series "The O.C." and "Arrow."
-
B.
Madeleine Stowe
Madeleine Stowe is an American actress best known for her film roles in the 1990s, including "The Last of the Mohicans" and "12 Monkeys," and later for her acclaimed television work.
-
C.
Deborah Anne Mazar
Deborah Anne Mazar is an American actress known for her sharp-tongued, tough-girl roles in film and television, including notable appearances in "Goodfellas," "Entourage," and "Younger."
-
D.
Jemima Kirke
Jemima Kirke is a British-American artist and actress best known for playing Jessa Johansson on the HBO series "Girls."
-
E.
Samara Weaving
Samara Weaving is an Australian actress known for her roles in film and television, particularly in horror-comedy and thriller projects such as "Ready or Not" and "The Babysitter."
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afa2e4a48190ba3c70013bab14f2 |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723b575a08190a3e0b1f233c36ba0 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 1:59 p.m.