Triple
T13567158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Jane Campion |
E324067
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Campion |
E322758
|
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: Campion | Statement: [Elizabeth Jane Campion, familyName, Campion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Campion Context triple: [Elizabeth Jane Campion, familyName, Campion]
-
A.
Campion
chosen
Campion is a surname most notably associated with New Zealand film director and screenwriter Jane Campion, acclaimed for works such as "The Piano."
-
B.
Spenser
Spenser is a tough, wisecracking Boston private investigator and the protagonist of Robert B. Parker’s long-running crime novel series.
-
C.
Chatterton
Chatterton is a small village in the Irwell Valley in Greater Manchester, England, known for its historic rural character and riverside setting.
-
D.
Sexton
Sexton is an English and Irish occupational surname historically given to church officers responsible for maintenance and burials.
-
E.
Hillegas
Hillegas is a surname most notably associated with Michael Hillegas, the first Treasurer of the United States.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00e0188819094fde44f85adb69c |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bb3d77c8190a7af2ee7e9b6748a |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.