Triple
T4917720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Demodocus |
E110387
|
entity |
| Predicate | typeOfCharacter |
P60013
|
FINISHED |
| Object | minor but symbolically important figure in the Odyssey |
—
|
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: minor but symbolically important figure in the Odyssey | Statement: [Demodocus, typeOfCharacter, minor but symbolically important figure in the Odyssey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCharacter Context triple: [Demodocus, typeOfCharacter, minor but symbolically important figure in the Odyssey]
-
A.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
B.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
C.
controllingCharacter
Indicates that one character exerts control, influence, or authority over another character.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
depictsCharacterType
Indicates that one entity visually represents or portrays a character of a specified type or role.
- 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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6fa760448190946401b4b21ea8b7 |
completed | March 20, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3421588190ab08e92b9558042e |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6e482984819087124216738f1e29 |
completed | March 20, 2026, 3:56 p.m. |
Created at: March 20, 2026, 1:29 p.m.