Triple
T3673965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara |
E77944
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Lara Pulver |
E159568
|
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: Lara Pulver | Statement: [Lara, hasNotableBearer, Lara Pulver]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lara Pulver Context triple: [Lara, hasNotableBearer, Lara Pulver]
-
A.
Lara Pulver
chosen
Lara Pulver is a British actress known for her roles in television series such as "Sherlock" and "Spooks," as well as various film and stage productions.
-
B.
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."
-
C.
Catherine Durkan
Catherine Durkan is a notable individual associated with the Durkan family name, recognized as a bearer of this surname.
-
D.
Kate Burton
Kate Burton is a British-American actress known for her work on stage and in television series such as "Grey's Anatomy" and "Scandal."
-
E.
Kate O'Mara
Kate O'Mara was a British actress best known for her glamorous, often villainous roles in television dramas such as Dynasty 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc45fbd1c819099023791452f1beb |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fafdfe108190a808364578d5edd1 |
completed | March 14, 2026, 6:06 a.m. |
Created at: March 8, 2026, 3:25 p.m.