Triple
T11696137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madison County |
E277998
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Wampsville |
E941140
|
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: Wampsville | Statement: [Madison County, hasVillage, Wampsville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wampsville Context triple: [Madison County, hasVillage, Wampsville]
-
A.
Wampsville
chosen
Wampsville is a small village in central New York State that serves as the county seat of Madison County.
-
B.
Yatesville
Yatesville is a small town located in the U.S. state of Georgia.
-
C.
Shingletown
Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
-
D.
Iverstown
Iverstown is the fictional, gloomy industrial town that serves as the central setting in the film noir drama "The Strange Love of Martha Ivers."
-
E.
Whitestown
Whitestown is a rapidly growing suburban town in Boone County, Indiana, located northwest of downtown Indianapolis within the greater Indianapolis metropolitan region.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47cef60819088b7cc3a3a711e4c |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef833084988190b5004c93f68dc628 |
completed | April 27, 2026, 3:39 p.m. |
Created at: April 8, 2026, 9:40 p.m.