Triple
T20990855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Biel |
E517019
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Biel |
—
|
NE NERFINISHED |
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: Biel | Statement: [Jessica Biel, familyName, Biel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biel Context triple: [Jessica Biel, familyName, Biel]
-
A.
Biel
chosen
Biel is a surname most prominently associated with American actress and producer Jessica Biel.
-
B.
Biel
Biel is a bilingual Swiss city in the canton of Bern known as a major center of the watchmaking industry and gateway to the Jura region.
-
C.
Biel-Benken
Biel-Benken is a small municipality in the canton of Basel-Landschaft in northwestern Switzerland, near the city of Basel and close to the French and German borders.
-
D.
Beyren
Beyren is a small village in eastern Luxembourg that forms part of the commune of Flaxweiler.
-
E.
Begna
Begna is a river in southeastern Norway that flows through the region of Ringerike and is known for its role in local hydropower production and freshwater ecosystems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fc1ba3d0819080d9d03817a45026 |
completed | April 21, 2026, 4:24 a.m. |
Created at: April 16, 2026, 1:50 p.m.