Triple
T3877902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Peterson |
E92548
|
entity |
| Predicate | voiceOf |
P2181
|
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: [Bob Peterson, voiceOf, Dug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dug Context triple: [Bob Peterson, voiceOf, 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.
Daggoo
Daggoo is a powerful African harpooner aboard the whaling ship Pequod in Herman Melville’s novel "Moby-Dick."
-
C.
Dodowa
Dodowa is a town in southern Ghana that serves as the capital of the Shai-Osudoku District and is known for its historic role in the Anglo-Ashanti wars and the nearby Dodowa Forest and waterfalls.
-
D.
Denguin
Denguin is a small commune in southwestern France, located in the Pyrénées-Atlantiques department in the Nouvelle-Aquitaine region.
-
E.
Banzi
Banzi is a town in the Basilicata region of southern Italy, known as the modern site near the ancient Lucanian city of Bantia.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec72fa7c81909c73b3cf90597e9a |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51251609c81909e19132475eb612d |
completed | March 14, 2026, 7:46 a.m. |
Created at: March 9, 2026, 3:20 p.m.