Triple
T29444469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernard Bernoulli |
E746810
|
entity |
| Predicate | otherProtagonistsInDayOfTheTentacle |
P76158
|
FINISHED |
| Object | Hoagie |
—
|
NE NERFINISHED |
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: Hoagie | Statement: [Bernard Bernoulli, otherProtagonistsInDayOfTheTentacle, Hoagie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherProtagonistsInDayOfTheTentacle Context triple: [Bernard Bernoulli, otherProtagonistsInDayOfTheTentacle, Hoagie]
-
A.
mainCharactersAre
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
B.
hasHumanProtagonists
Indicates that the primary characters driving the narrative are human beings rather than non-human entities.
-
C.
associatedCharacters
chosen
Indicates that two or more characters are linked or connected through some relationship, involvement, or relevance to each other.
-
D.
characters
Indicates that one entity is a character (or set of characters) associated with, appearing in, or belonging to another entity (such as a work, story, or medium).
-
E.
trineCompanions
Indicates that two entities are companions whose relationship is characterized by a harmonious or complementary trine-like alignment.
- F. None of above.
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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 28, 2026, 3:26 p.m.