Triple
T15115244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara Bosson |
E361018
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Hooperman |
E368311
|
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: Hooperman | Statement: [Barbara Bosson, notableWork, Hooperman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hooperman Context triple: [Barbara Bosson, notableWork, Hooperman]
-
A.
Hooperman
chosen
Hooperman is an American television dramedy series from the late 1980s starring John Ritter as a San Francisco police inspector balancing his personal and professional life.
-
B.
Hannen
Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
-
C.
Carver
Carver is the given name of Carver A. Mead, a pioneering American electrical engineer and computer scientist known for his foundational work in microelectronics and VLSI design.
-
D.
Carver
Carver is a small town in southeastern Massachusetts known for its cranberry bogs and rural character.
-
E.
Carver
Carver is a common shorthand name for Carver-Hawkeye Arena, the University of Iowa’s primary indoor sports venue.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058f4fb88190a3d446a466aebcf1 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7eee6e8819092657c4006456135 |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:05 a.m.