Triple
T19233443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Lautenberg |
E480928
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Frank |
—
|
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: Frank | Statement: [Frank Lautenberg, givenName, Frank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Context triple: [Frank Lautenberg, givenName, Frank]
-
A.
Frank
chosen
Frank is the given name of Frank Lautenberg, a long-serving United States Senator from New Jersey known for his work on public health and transportation safety.
-
B.
Frank
Frank is the nickname of Frank Sheeran, an American labor union official and alleged mob hitman whose life inspired the film "The Irishman."
-
C.
Frank
Frank is the given name of Frank Herbert, the renowned American science fiction author best known for writing the novel "Dune."
-
D.
Frank
Frank is the given name of the American comic book writer, artist, and film director Frank Miller, known for works like "The Dark Knight Returns," "Sin City," and "300."
-
E.
Frank
Frank is the given name of Frank Brangwyn, a renowned British painter, muralist, and designer associated with the Arts and Crafts movement.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa9fa7348190947129273d19c9a7 |
completed | April 20, 2026, 10:06 a.m. |
Created at: April 10, 2026, 1:26 p.m.