Triple
T10949389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven Campbell |
E258685
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Campbell |
E218281
|
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: Campbell | Statement: [Steven Campbell, familyName, Campbell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Campbell Context triple: [Steven Campbell, familyName, Campbell]
-
A.
Campbell
Campbell is a small suburban city in California’s Silicon Valley, known as the original home of eBay and for its vibrant downtown and community events.
-
B.
Campbell
chosen
Campbell is a common Scottish surname historically associated with the powerful Clan Campbell of the Scottish Highlands.
-
C.
Mathison
Mathison is a surname most notably associated with American screenwriter Melissa Mathison, known for writing the screenplay for "E.T. the Extra-Terrestrial."
-
D.
Brewster
Brewster is an English occupational surname historically associated with brewing ale or beer.
-
E.
Brewster
Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ec7028819084f5ce2035a128e4 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d733f7d88190b45df5c155ff5a46 |
completed | April 18, 2026, 12:58 a.m. |
Created at: April 8, 2026, 9:23 p.m.