Triple
T19957855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Milton |
E479731
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Thame |
—
|
NE NERFINISHED |
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: Thame | Statement: [Great Milton, locatedNear, Thame]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thame Context triple: [Great Milton, locatedNear, Thame]
-
A.
Thame
chosen
Thame is a historic market town in Oxfordshire, England, known for its traditional architecture and vibrant local community.
-
B.
Thame
Thame is a remote Sherpa village in Nepal’s Khumbu region, known as a traditional trading settlement and trekking stop on the route toward the high Himalayas.
-
C.
Tshela
Tshela is a town in the western Democratic Republic of the Congo, situated in the forested interior of Kongo Central Province near the border with the Republic of the Congo.
-
D.
Vaal
Vaal is a powerful, god-like computer entity that controls a primitive society in the Star Trek: The Original Series episode "The Apple."
-
E.
Gatenga
Gatenga is an urban sector within Kigali, Rwanda, known for its residential neighborhoods and local commercial activity.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65af1b32c81908ebe0e2570ec06a9 |
completed | April 20, 2026, 4:57 p.m. |
Created at: April 10, 2026, 1:54 p.m.