Triple
T15207640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Forbat |
E363429
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Fred Forbat |
E363429
|
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: Fred Forbat | Statement: [Fred Forbat, name, Fred Forbat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Forbat Context triple: [Fred Forbat, name, Fred Forbat]
-
A.
Fred Forbat
chosen
Fred Forbat was a Hungarian-born modernist architect and urban planner associated with the Bauhaus movement and influential European social housing projects.
-
B.
Frank Boucher
Frank Boucher was a Canadian Hall of Fame ice hockey centre and coach best known for his stellar play with the New York Rangers in the NHL.
-
C.
Frank Gibeau
Frank Gibeau is an American video game executive known for his leadership roles at major gaming companies, including serving as CEO of Zynga and holding senior positions at Electronic Arts.
-
D.
Leon Barmore
Leon Barmore is a legendary women's college basketball coach best known for leading the Louisiana Tech Lady Techsters to national prominence and multiple NCAA championships.
-
E.
William Froug
William Froug was an American television producer, writer, and educator best known for his work on classic series such as The Twilight Zone.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b8e2788190bd1831762e4181ae |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd2f86688190bafdfe72033eda90 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:11 a.m.