Triple
T6954412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crisis |
E161205
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Rachael Taylor |
E385714
|
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: Rachael Taylor | Statement: [Crisis, starring, Rachael Taylor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachael Taylor Context triple: [Crisis, starring, Rachael Taylor]
-
A.
Rachael Taylor
chosen
Rachael Taylor is an Australian actress known for her roles in films like "Transformers" and TV series such as "Jessica Jones."
-
B.
Rachel Taylor
Rachel Taylor was the second wife of acclaimed American actor Jason Robards, with whom she was married in the mid-20th century.
-
C.
Rachael Stirling
Rachael Stirling is a British actress known for her work in television, film, and theatre, including prominent roles in series such as "Detectorists" and "Tipping the Velvet."
-
D.
Rachael MacFarlane
Rachael MacFarlane is an American voice actress and singer best known for her work on animated television series, including voicing Hayley Smith on "American Dad!"
-
E.
Lindsay Duncan
Lindsay Duncan is a Scottish actress acclaimed for her work on stage, film, and television, known for roles in productions such as "About Time," "Rome," and "Doctor Who."
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dace1a94819095311e4288f01784 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7753f1fe08190a734e371db4d1d38 |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:29 p.m.