Triple
T3378332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth Sladen |
E71119
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Elisabeth Sladen |
E71119
|
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: Elisabeth Sladen | Statement: [Elisabeth Sladen, name, Elisabeth Sladen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elisabeth Sladen Context triple: [Elisabeth Sladen, name, Elisabeth Sladen]
-
A.
Elisabeth Sladen
chosen
Elisabeth Sladen was an English actress best known for playing the beloved Doctor Who companion Sarah Jane Smith across multiple series and spin-offs.
-
B.
Katy Manning
Katy Manning is a British actress best known to Doctor Who fans for playing the Third Doctor’s companion Jo Grant in the early 1970s.
-
C.
Sheila Hancock
Sheila Hancock is a British actress and author renowned for her extensive work in theatre, television, and film, as well as her appearances as a television presenter and panelist.
-
D.
Victoria Tennant
Victoria Tennant is a British actress known for her work in film and television, including roles in "L.A. Story" and the miniseries "The Winds of War."
-
E.
Jane Wenham
Jane Wenham was a British actress known for her work in mid-20th-century film, television, and theatre.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2eacb5c81908071a1dacc9a897a |
completed | March 8, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bc17dd881908fc5fb0d4a23f40f |
completed | March 12, 2026, 11:26 p.m. |
Created at: March 8, 2026, 3:14 p.m.