Triple
T4218656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Zients |
E94283
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Zients |
E94283
|
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: Zients | Statement: [Jeff Zients, familyName, Zients]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zients Context triple: [Jeff Zients, familyName, Zients]
-
A.
Zients
chosen
Zients is the surname of Jeff Zients, an American businessman and government official who has served in senior economic and management roles in the U.S. federal government.
-
B.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
C.
Orzola
Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
-
D.
Zinovy
Zinovy is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
-
E.
Lontzen
Lontzen is a municipality in eastern Belgium, located in the country’s German-speaking region near the border with Germany.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5963d3bd8819086465701f4c6adf5 |
completed | March 14, 2026, 5:09 p.m. |
Created at: March 12, 2026, 11:04 p.m.