Triple
T15661596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Boren |
E376578
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Boren |
E376578
|
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: Boren | Statement: [David Boren, hasFamilyName, Boren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boren Context triple: [David Boren, hasFamilyName, Boren]
-
A.
Boren
chosen
Boren is a surname most prominently associated with American politician and former Oklahoma governor and U.S. senator David Boren.
-
B.
Toole
Toole is the surname of American actress, dancer, and singer-songwriter Annette O'Toole, known for her roles in film and television since the 1970s.
-
C.
Boerne
Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
-
D.
Tolan
Tolan is a surname most notably associated with American television producer, writer, and director Peter Tolan.
-
E.
Northern State
Northern State is a sparsely populated administrative region in northern Sudan that encompasses much of the Nubian Desert and stretches along the Nile River.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef4e6a08190ad8bbafaa3612f22 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ed6f50c81909d87ced263064f0d |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 4:15 a.m.