Triple
T16247035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Churchland |
E394396
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Churchland |
E898991
|
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: Churchland | Statement: [Paul Churchland, familyName, Churchland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Churchland Context triple: [Paul Churchland, familyName, Churchland]
-
A.
Churchland
chosen
Churchland is the surname of Patricia Churchland, a prominent philosopher known for her work in neurophilosophy and the philosophy of mind.
-
B.
Kelling
Kelling is a small coastal village in Norfolk, England, known for its scenic heathland, wildlife, and proximity to the North Sea.
-
C.
Marford
Marford is a village in Wrexham County Borough, Wales, known for its distinctive Gothic-style architecture and historic character.
-
D.
Sharswood
Sharswood is a residential neighborhood in North Philadelphia known for its ongoing redevelopment and proximity to areas like Brewerytown and Girard College.
-
E.
Gooding
Gooding is a small city in south-central Idaho known historically for its agricultural roots and role in the region’s dairy 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245931074819096f38003da70f271 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ee3bbc48190a56ce2807a9510f0 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.