Triple
T28307176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gowther Mossock |
E713889
|
entity |
| Predicate | helpsProtagonists |
P49758
|
FINISHED |
| Object | by offering shelter |
—
|
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: by offering shelter | Statement: [Gowther Mossock, helpsProtagonists, by offering shelter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsProtagonists Context triple: [Gowther Mossock, helpsProtagonists, by offering shelter]
-
A.
helpsProtagonistWith
chosen
Indicates that one entity assists the protagonist in performing, achieving, or dealing with something specified by the other entity.
-
B.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
C.
hasHumanProtagonists
Indicates that the primary characters driving the narrative are human beings rather than non-human entities.
-
D.
protagonistBasedOn
Indicates that a fictional work’s main character is modeled on, inspired by, or derived from a particular real or fictional person or entity.
-
E.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
- 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_69efb5256afc8190b9322d25c3ae6320 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 11:38 p.m.