Triple
T9754772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell |
E236526
|
entity |
| Predicate | friendOf |
P8712
|
FINISHED |
| Object | Dug |
E236527
|
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: Dug | Statement: [Russell, friendOf, Dug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dug Context triple: [Russell, friendOf, Dug]
-
A.
Dug
chosen
Dug is the lovable, talking golden retriever from Pixar's animated film "Up," known for his collar that translates his thoughts into speech and his enthusiastic, friendly personality.
-
B.
Digger
Digger was the nickname of Al Cervi, a Hall of Fame American professional basketball player and coach known for his tough, hard-nosed style of play in the early NBA.
-
C.
Digger
Digger is the central character of the play "The Hasty Heart," around whom the story’s emotional and dramatic developments revolve.
-
D.
Tobo
Tobo is a small locality in eastern Sweden situated within Tierp Municipality in Uppsala County.
-
E.
Dino
Dino is a masculine given name of Italian origin, commonly used as a short form of names like Bernardino or Gherardino.
- 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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9fb1370c8190bc153db8cababc62 |
completed | April 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcd60e1c81908ea2e38ca91e58f6 |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:24 p.m.