Triple
T12887368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sachse, Texas |
E308263
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | William Sachse |
E160080
|
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: William Sachse | Statement: [Sachse, Texas, namedAfter, William Sachse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Sachse Context triple: [Sachse, Texas, namedAfter, William Sachse]
-
A.
William Sachse
chosen
William Sachse was a 19th-century Texas pioneer and landowner after whom the city of Sachse, Texas, is named.
-
B.
William Diehl
William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
-
C.
William Scheves
William Scheves was a 15th-century Scottish churchman who became Archbishop of St Andrews and a prominent figure in the late medieval Scottish Church.
-
D.
Karl Schaefer
Karl Schaefer is a television writer and producer best known for co-creating the zombie apocalypse series Z Nation and its Netflix prequel Black Summer.
-
E.
Herbert Sattler
Herbert Sattler is an individual notable enough to be recognized as a namesake bearer of the surname Sattler.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714415c08190aa9944b494a3ddad |
completed | April 10, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec869957481909ea4fded01851b70 |
completed | May 9, 2026, 5:38 a.m. |
Created at: April 9, 2026, 5:39 p.m.