Triple
T4307977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Human Comedy |
E94001
|
entity |
| Predicate | notableCharacterOccupation |
P56368
|
FINISHED |
| Object | telegraph messenger |
—
|
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: telegraph messenger | Statement: [The Human Comedy, notableCharacterOccupation, telegraph messenger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCharacterOccupation Context triple: [The Human Comedy, notableCharacterOccupation, telegraph messenger]
-
A.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
B.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
C.
notableCharacterType
Indicates that an entity is a notable or prominent example of a specified character type or role.
-
D.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
E.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
- F. None of above. chosen
Provenance (4 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_69b3451886588190a3dd1305ea7c58dc |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b350d2af088190ad7cb035d6e0f8c2 |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b34f4a07b08190a06ada0d9cbb14fb |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:11 p.m.