Triple
T14893851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lew Burdette |
E359818
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Burdette |
E1182208
|
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: Burdette | Statement: [Lew Burdette, familyName, Burdette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burdette Context triple: [Lew Burdette, familyName, Burdette]
-
A.
Burdette
chosen
Burdette is a surname most notably associated with Lew Burdette, a prominent Major League Baseball pitcher of the mid-20th century.
-
B.
Beeville
Beeville is a small city in southern Texas known as the county seat of Bee County and home to Coastal Bend College.
-
C.
Wimberley
Wimberley is a small, scenic town in central Texas known for its picturesque Hill Country landscapes, swimming holes, and artsy, tourist-friendly downtown.
-
D.
Corsicana
Corsicana is a small city in north-central Texas known for its oil boom history and as a regional commercial and transportation hub between Dallas and Houston.
-
E.
Crosbyton
Crosbyton is a small rural city in West Texas that serves as the administrative and commercial hub of Crosby County.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f9d10c819091732d7a5a42a682 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb590b5cc8190b5f586e0fd2988f6 |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 2:10 a.m.