Triple
T17300422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Godiva |
E420024
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Coventry |
E14847
|
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: Coventry | Statement: [Lady Godiva, residence, Coventry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coventry Context triple: [Lady Godiva, residence, Coventry]
-
A.
Coventry
chosen
Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
-
B.
Coventry
Coventry is a town in central Rhode Island known for its suburban communities, historic villages, and extensive outdoor recreation areas.
-
C.
Nottingham
Nottingham is a major city in the East Midlands of England, historically known for its lace-making and bicycle industries and famously associated with the legend of Robin Hood.
-
D.
Wolverhampton
Wolverhampton is a large industrial city in England’s West Midlands, known historically for its role in the coal, steel, and manufacturing industries.
-
E.
Leicester
Leicester is a small rural town in Addison County, Vermont, known for its scenic New England landscape and proximity to Lake Dunmore.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e438f9e5ac8190ba0b5820790112d9 |
completed | April 19, 2026, 2:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180da5b808190857c51aaa2e85339 |
completed | May 11, 2026, 7:10 a.m. |
Created at: April 10, 2026, 5:41 a.m.