Triple
T5765940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenesaw Mountain Landis |
E127213
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Landis |
E127213
|
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: Landis | Statement: [Kenesaw Mountain Landis, hasSurname, Landis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landis Context triple: [Kenesaw Mountain Landis, hasSurname, Landis]
-
A.
Landis
chosen
Landis is a surname most famously associated with Kenesaw Mountain Landis, the first Commissioner of Major League Baseball known for his role in restoring public confidence after the Black Sox Scandal.
-
B.
Espee
Espee is a common nickname for the historic Southern Pacific Railroad, a major American railroad that operated in the western United States.
-
C.
Farris
Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
-
D.
Lance
Lance is a snack food brand best known for its sandwich crackers and other packaged snack products.
-
E.
Lance
Lance is a masculine given name of Germanic origin commonly used in English-speaking countries.
- 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_69c00834f6308190851b0abeddd8ed7e |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02970db3481908a06941c9d59cc86 |
completed | March 22, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e5d8c8c819081067de808ac1b56 |
completed | March 22, 2026, 11:42 p.m. |
Created at: March 22, 2026, 3:49 p.m.