Triple
T29587110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Valjean (Volume V) |
E754048
|
entity |
| Predicate | roleForCosette |
P167484
|
FINISHED |
| Object | adoptive father |
—
|
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: adoptive father | Statement: [Jean Valjean (Volume V), roleForCosette, adoptive father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleForCosette Context triple: [Jean Valjean (Volume V), roleForCosette, adoptive father]
-
A.
roleInCoco
Indicates that an entity serves a specific role or function within the context of the COCO dataset or framework.
-
B.
roleAccordingTo
Indicates that an entity holds a particular role or function as defined or interpreted by a specified source or perspective.
-
C.
roleOfCharacter
Indicates that one entity serves as the narrative or functional role played by a character within a story, scenario, or context.
-
D.
designedRole
Indicates that one entity has been created, configured, or intended to serve a particular function, purpose, or role in relation to another entity.
-
E.
roleForProtagonist
Indicates the specific narrative or functional role that an entity plays in relation to the story’s main protagonist.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d7f46c481908cab81ff3be2b98b |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 28, 2026, 6:11 p.m.