Triple
T3236876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velvet Goldmine |
E67874
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Billie Whitelaw |
E72700
|
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: Billie Whitelaw | Statement: [Velvet Goldmine, starring, Billie Whitelaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billie Whitelaw Context triple: [Velvet Goldmine, starring, Billie Whitelaw]
-
A.
Billie Whitelaw
chosen
Billie Whitelaw was an acclaimed English actress renowned for her intense stage and screen performances, particularly in the plays of Samuel Beckett.
-
B.
Peggy Ashcroft
Peggy Ashcroft was a distinguished English stage and film actress renowned for her Shakespearean performances and her long, influential career in British theatre.
-
C.
Celia Johnson
Celia Johnson was a distinguished English actress best known for her nuanced, understated performances in classic British films such as "Brief Encounter."
-
D.
Edith Lesley
Edith Lesley was an American educator and founder of the teacher-training institution that evolved into Lesley University in Cambridge, Massachusetts.
-
E.
Flora Robson
Flora Robson was a distinguished British actress known for her powerful character roles in both stage and film, often portraying strong, authoritative women.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef29bf48190a9aa3a39f0138428 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b367e780008190b554bf1ad0c7cc59 |
completed | March 13, 2026, 1:27 a.m. |
Created at: March 8, 2026, 3:08 p.m.