Triple
T13863291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobias Enström |
E333253
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Enström |
E333253
|
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: Enström | Statement: [Tobias Enström, familyName, Enström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enström Context triple: [Tobias Enström, familyName, Enström]
-
A.
Enström
chosen
Enström is a Swedish surname most notably associated with professional ice hockey player Tobias Enström.
-
B.
Edström
Edström is a Swedish surname borne by several notable figures, including athletes, politicians, and industrial leaders.
-
C.
Sundström
Sundström is a Swedish surname borne by various notable individuals, including actress Rebecca Ferguson.
-
D.
Bäckström
Bäckström is a Swedish surname most prominently associated with NHL ice hockey star Nicklas Bäckström.
-
E.
Lindström
Lindström is a Swedish surname borne by various notable individuals in fields such as the arts, sports, and politics.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c30d9c81908217d41a3b4aaf85 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0ff1f78819088ae58f703e2c9ff |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.