Triple
T10907015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Din Djarin |
E257598
|
entity |
| Predicate | helmetPolicy |
P96343
|
FINISHED |
| Object | does not remove helmet in front of others by creed |
—
|
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: does not remove helmet in front of others by creed | Statement: [Din Djarin, helmetPolicy, does not remove helmet in front of others by creed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helmetPolicy Context triple: [Din Djarin, helmetPolicy, does not remove helmet in front of others by creed]
-
A.
helmetType
Indicates the specific category or style of helmet associated with an entity.
-
B.
helmetNumber
Indicates the identifying number assigned to a person or object as displayed on their helmet.
-
C.
helmetLogo
Indicates that one entity serves as the logo or emblem displayed on the helmet of another entity.
-
D.
helmetColor
Indicates the specific color attribute assigned to a helmet in the relationship.
-
E.
woreHelmetOf
Indicates that one entity used or was equipped with the helmet that belongs to or is associated with another entity.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7706756d081908ed29c68d81df688 |
completed | April 9, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101de31c819090707635f6790559 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:22 p.m.