Triple
T9847701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doo-Dah |
E239383
|
entity |
| Predicate | appliesTo |
P1129
|
FINISHED |
| Object | Wichita |
E149269
|
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: Wichita | Statement: [Doo-Dah, appliesTo, Wichita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wichita Context triple: [Doo-Dah, appliesTo, Wichita]
-
A.
Wichita
Wichita is a 1955 American Western film starring Joel McCrea as lawman Wyatt Earp in the turbulent Kansas cattle town.
-
B.
Wichita
Wichita is a savvy, resourceful con artist and one of the central survivors in the post-apocalyptic comedy film "Zombieland."
-
C.
Wichita
Wichita is a small unincorporated community located in Guthrie County, Iowa.
-
D.
Wichita, Kansas
chosen
Wichita, Kansas is the largest city in the state of Kansas, known as a major center for the U.S. aircraft industry and situated in south-central Kansas along the Arkansas River.
-
E.
Topeka, Kansas
Topeka, Kansas is the capital city of the U.S. state of Kansas, historically significant as the community at the center of the landmark school desegregation case Brown v. Board of Education.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb362d81081908f41cc25baca5fda |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d299c51ea08190902e03552fbe7ebb |
completed | April 5, 2026, 5:20 p.m. |
Created at: March 30, 2026, 8:34 p.m.