Triple
T20488507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Ross |
E502675
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Frank Ross |
—
|
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 Ross | Statement: [Frank Ross, name, Frank Ross]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Ross Context triple: [Frank Ross, name, Frank Ross]
-
A.
Frank Ross
chosen
Frank Ross is a fictional rancher whose murder sets the revenge-driven plot in Charles Portis's novel "True Grit" into motion.
-
B.
Frank Ross
Frank Ross was an American film producer known for his work on major mid-20th-century Hollywood productions.
-
C.
William Ross
William Ross is an American composer, orchestrator, and conductor known for his work on numerous film scores and collaborations with major Hollywood productions.
-
D.
Charles Wood
Charles Wood was an Irish-born composer and influential teacher associated with the English Musical Renaissance, best known for his Anglican church music and role in shaping early 20th-century British composers.
-
E.
Charles Wood
Charles Wood was a British playwright and screenwriter known for his sharp, satirical writing and influential work in film, television, and theatre.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b5c6f84819087d813be3542ed33 |
completed | April 20, 2026, 9:32 p.m. |
Created at: April 16, 2026, 11:34 a.m.