Triple
T6776381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mules |
E155165
|
entity |
| Predicate | homeCity |
P263
|
FINISHED |
| Object | Warrensburg |
E296730
|
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: Warrensburg | Statement: [Mules, homeCity, Warrensburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warrensburg Context triple: [Mules, homeCity, Warrensburg]
-
A.
Warrensburg, Missouri
chosen
Warrensburg, Missouri is a small central Missouri city best known as the home of the University of Central Missouri and its college-town community.
-
B.
Warrenton
Warrenton is a small historic town in Fauquier County that serves as a commercial and civic hub for the surrounding rural areas of Northern Virginia.
-
C.
Tompkinsville
Tompkinsville is a waterfront neighborhood on Staten Island in New York City, known for its diverse community and proximity to the St. George ferry terminal.
-
D.
Maryville
Maryville is a small city in northwest Missouri best known as the home of Northwest Missouri State University.
-
E.
Yatesville
Yatesville is a small town located in the U.S. state of Georgia.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d24f77c88190be21cf4ef132aa31 |
completed | March 27, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7510e26148190a75e660cedf1274e |
completed | March 28, 2026, 3:54 a.m. |
Created at: March 27, 2026, 2:13 p.m.