Triple
T19741384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Colbert |
E474127
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Rachel Colbert |
—
|
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: Rachel Colbert | Statement: [Rachel Colbert, hasName, Rachel Colbert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Colbert Context triple: [Rachel Colbert, hasName, Rachel Colbert]
-
A.
Rachel Colbert
chosen
Rachel Colbert is the protagonist of the novel "Sapphira and the Slave Girl," around whom the story’s exploration of race, power, and morality in antebellum Virginia revolves.
-
B.
Elizabeth Prall
Elizabeth Prall was an American bookseller and literary figure best known for her marriage to modernist writer Sherwood Anderson.
-
C.
Rachel Scheer
Rachel Scheer is an actress known for her role in the horror film "The Rage."
-
D.
Emily Berrington
Emily Berrington is a British actress best known for her role as the synth Niska in the television series "Humans."
-
E.
Rebecca Cottrell
Rebecca Cottrell is the wife of Stephen Cottrell, the Archbishop of York in the Church of England.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6516159c8819090022094aa91902b |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.