Triple
T10453234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Solemani |
E246485
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sarah Solemani |
E246485
|
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: Sarah Solemani | Statement: [Sarah Solemani, name, Sarah Solemani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Solemani Context triple: [Sarah Solemani, name, Sarah Solemani]
-
A.
Sarah Solemani
chosen
Sarah Solemani is a British actress and writer known for her roles in television comedies like "Him & Her" and "Bad Education" as well as various film and stage performances.
-
B.
Sussan Tahmasebi
Sussan Tahmasebi is an Iranian women's rights activist and civil society leader known for her advocacy against discriminatory laws and her role in grassroots reform movements.
-
C.
Hedieh Tehrani
Hedieh Tehrani is a prominent Iranian film actress acclaimed for her intense, nuanced performances in contemporary Iranian cinema.
-
D.
Sediqa Massoud
Sediqa Massoud is the widow of famed Afghan resistance leader Ahmad Shah Massoud and a prominent advocate for women's rights and education in Afghanistan.
-
E.
Shahrzad Davani
Shahrzad Davani is a film producer best known for her work on the biographical drama "Brain on Fire."
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0d73d48190acb687b96918e0cf |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87f07c9f48190b0fce7740a2e003a |
completed | April 10, 2026, 4:39 a.m. |
Created at: April 6, 2026, 12:17 p.m.