Triple
T13992648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prima Facie |
E336618
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Tessa Ensler |
E442709
|
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: Tessa Ensler | Statement: [Prima Facie, mainCharacter, Tessa Ensler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Ensler Context triple: [Prima Facie, mainCharacter, Tessa Ensler]
-
A.
Tessa Ensler
chosen
Tessa Ensler is a character portrayed by Jodie Comer, likely in a dramatic screen or stage production.
-
B.
Tessa Ross
Tessa Ross is a prominent British film and television producer known for backing acclaimed, often auteur-driven projects across UK cinema and high-end TV drama.
-
C.
Tessa Sanger
Tessa Sanger is the passionate, musically gifted young heroine of Margaret Kennedy’s novel "The Constant Nymph," whose intense, unconventional love and emotional vulnerability drive much of the story’s drama.
-
D.
Tessa Berens
Tessa Berens is a fictional character from the work titled "The Silence."
-
E.
Sarah Climenhaga
Sarah Climenhaga is a Toronto-based activist and community advocate who ran as a candidate in the city’s 2018 mayoral election, focusing on issues like civic engagement, sustainability, and safer streets.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb3b5d881909f15a1e08bb202f3 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd54fa19c081908e6467ee7b79f02a |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 9, 2026, 10:19 p.m.