Triple
T20104570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ida Straus |
E486963
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Straus |
—
|
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: Straus | Statement: [Ida Straus, familyName, Straus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Straus Context triple: [Ida Straus, familyName, Straus]
-
A.
Straus
chosen
Straus is a German-origin surname notably borne by Isidor Straus, the American businessman and co-owner of Macy’s who perished on the Titanic.
-
B.
Fisher
Fisher is a common English surname borne by numerous notable individuals across fields such as economics, politics, entertainment, and sports.
-
C.
Dunnigan
Dunnigan is a small unincorporated community in Yolo County, California, known primarily as a rural agricultural area along Interstate 5.
-
D.
De Ross
De Ross is a surname that may refer to various individuals, often of European origin, and can appear with different capitalization or spacing variants.
-
E.
Dusenberry
Dusenberry is a surname of English origin borne by various individuals, including American actress Ann Dusenberry.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666daf73c819089f02ca6faa2c283 |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:27 p.m.