Triple
T10470469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomorrow Never Dies |
E246909
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Teri Hatcher |
E109876
|
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: Teri Hatcher | Statement: [Tomorrow Never Dies, starring, Teri Hatcher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teri Hatcher Context triple: [Tomorrow Never Dies, starring, Teri Hatcher]
-
A.
Teri Hatcher
chosen
Teri Hatcher is an American actress best known for her roles on the television series "Lois & Clark: The New Adventures of Superman" and "Desperate Housewives."
-
B.
Elizabeth Berkley
Elizabeth Berkley is an American actress best known for her roles in the TV series "Saved by the Bell" and the film "Showgirls."
-
C.
Angela Richards
Angela Richards is known as one of the children of Rolling Stones guitarist Keith Richards.
-
D.
Nicollette Sheridan
Nicollette Sheridan is a British-American actress best known for her roles on the television series "Knots Landing" and "Desperate Housewives."
-
E.
Cybill Shepherd
Cybill Shepherd is an American actress and former model best known for her roles in films like "The Last Picture Show" and the TV series "Moonlighting."
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a0094910819094d492c87b31898e |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.