Triple
T16270981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Elementary School |
E394997
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Wamego |
E398633
|
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: Wamego | Statement: [West Elementary School, city, Wamego]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wamego Context triple: [West Elementary School, city, Wamego]
-
A.
Wamego
chosen
Wamego is a small Kansas city known for its strong connection to The Wizard of Oz, including themed attractions and annual celebrations.
-
B.
Pumanque
Pumanque is a rural municipality and town in central Chile’s O’Higgins Region, known for its agricultural activities within the Colchagua Valley area.
-
C.
Sariaya
Sariaya is a historic coastal municipality in the province of Quezon, Philippines, known for its heritage houses, agricultural produce, and beaches along Tayabas Bay.
-
D.
Quillacingas
Quillacingas refers to an Indigenous people of the Andean region of present-day Colombia, historically known for their distinct culture, language, and resistance to Spanish colonization.
-
E.
Tortosendo
Tortosendo is a civil parish in the municipality of Covilhã in central Portugal, known historically for its textile industry.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e246099dd081908e268a1a0cf8a373 |
completed | April 17, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017bf09888190b3d90db3517a2f1e |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:05 a.m.