Triple
T6526984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swarm |
E151328
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Sara Esberg |
E151328
|
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: Sara Esberg | Statement: [Swarm, executiveProducer, Sara Esberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Esberg Context triple: [Swarm, executiveProducer, Sara Esberg]
-
A.
Sara Esberg
chosen
Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
-
B.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
-
C.
Åsa Larsson
Åsa Larsson is a Swedish crime fiction author best known for her Rebecka Martinsson series set in northern Sweden.
-
D.
Pia Lindström
Pia Lindström is a Swedish-American television journalist and critic, best known as the eldest daughter of legendary actress Ingrid Bergman.
-
E.
Helena Seger
Helena Seger is a Swedish businesswoman and former model best known as the long-term partner of footballer Zlatan Ibrahimović.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ada8a0e48190947616f3a09a2cba |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d5271b7c8190a602f6ec72efe04c |
completed | March 27, 2026, 7:06 p.m. |
Created at: March 27, 2026, 1:45 p.m.