Triple
T2732350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob (TV series) |
E60342
|
entity |
| Predicate | workLocationOfCharacter |
P1527
|
FINISHED |
| Object | comic book publishing company |
—
|
LITERAL 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: comic book publishing company | Statement: [Bob (TV series), workLocationOfCharacter, comic book publishing company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLocationOfCharacter Context triple: [Bob (TV series), workLocationOfCharacter, comic book publishing company]
-
A.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
-
B.
workBasedOnThisCharacter
Indicates that a creative work is based on, inspired by, or derived from the referenced character.
-
C.
propertyLocation
Indicates the geographical place or address where a property is situated or found.
-
D.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
E.
locationOfWork
chosen
Indicates the place or site where an entity performs its work or carries out its professional activities.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaf011548190beb9c3feee7b743f |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.