Triple
T21898530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Lapp |
E540746
|
entity |
| Predicate | formsBondWith |
P68132
|
FINISHED |
| Object | John Book |
—
|
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: John Book | Statement: [Rachel Lapp, formsBondWith, John Book]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Book Context triple: [Rachel Lapp, formsBondWith, John Book]
-
A.
John Book
chosen
John Book is the tough, principled Philadelphia detective who goes undercover in an Amish community to protect a young murder witness in the film "Witness."
-
B.
Will Parker
Will Parker is a cheerful, somewhat naive cowboy and rodeo performer who provides comic relief and romantic subplots in the classic Rodgers and Hammerstein musical "Oklahoma!".
-
C.
Elias Pearce
Elias Pearce was the mountaineer credited with making the first recorded ascent of Mount Shasta in California.
-
D.
John Cross
John Cross is a former Australian rugby league footballer best known for his time as a forward with the Illawarra Steelers in the NSWRL/ARL.
-
E.
Axel Foley
Axel Foley is the wisecracking, street-smart Detroit detective and main protagonist of the "Beverly Hills Cop" film series.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc8c2108190b55ff1ba3badc9fb |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:07 p.m.