Triple
T6099762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunga Din |
E135963
|
entity |
| Predicate | characterRoleOfGungaDin |
P23263
|
FINISHED |
| Object | water-bearer |
—
|
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: water-bearer | Statement: [Gunga Din, characterRoleOfGungaDin, water-bearer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfGungaDin Context triple: [Gunga Din, characterRoleOfGungaDin, water-bearer]
-
A.
featuresCharacterRole
chosen
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
B.
roleInFilmEcosystem
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
-
C.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
D.
genreRole
Indicates a relationship where an entity holds a specific functional or categorical role within a particular genre.
-
E.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3970808190ba90f5e4235db9f2 |
completed | March 22, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c049f5ac988190b62ba565153aaa35 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.