Triple
T6080289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esther Acebo |
E135505
|
entity |
| Predicate | portrays |
P264
|
FINISHED |
| Object | Stockholm |
E115002
|
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: Stockholm | Statement: [Esther Acebo, portrays, Stockholm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stockholm Context triple: [Esther Acebo, portrays, Stockholm]
-
A.
Stockholm
Stockholm is the capital city of Sweden, renowned for its historic architecture, cultural institutions, and role as a major political, economic, and scientific center in Scandinavia.
-
B.
Stockholm
chosen
Stockholm is a fictional character in the Spanish television series "Money Heist" (La Casa de Papel), known for evolving from a hostage to a member of the heist crew.
-
C.
Gothenburg
Gothenburg is a small city in western Nebraska known for its historic Pony Express station and classic Midwestern agricultural community.
-
D.
Gothenburg
Gothenburg is Sweden’s second-largest city, a major port on the country’s west coast known for its maritime heritage, universities, and vibrant cultural scene.
-
E.
Stockholm Värtahamnen
Stockholm Värtahamnen is a major ferry and cargo terminal area in northeastern central Stockholm, serving both domestic and international maritime traffic.
- 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057735b6081908b82757505fa7d5d |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64b8e4dd88190be82d6e5ad9f2e7a |
completed | March 27, 2026, 9:19 a.m. |
Created at: March 22, 2026, 4:11 p.m.