Triple
T509393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2 train |
E10571
|
entity |
| Predicate | serviceDesignationStyle |
P12359
|
FINISHED |
| Object | number in red circle |
—
|
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: number in red circle | Statement: [2 train, serviceDesignationStyle, number in red circle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceDesignationStyle Context triple: [2 train, serviceDesignationStyle, number in red circle]
-
A.
serviceUniform
Indicates that one entity is wearing or associated with a standardized uniform used for official or professional service.
-
B.
usedWithStyle
Indicates that something is employed or applied in conjunction with a particular style or stylistic manner.
-
C.
isStyleOfAddress
Indicates that one term or expression functions as a particular way of addressing or referring to another entity.
-
D.
designatorType
chosen
Indicates the specific role or category of a designator used to identify or reference an entity within a system or context.
-
E.
designationUsedFor
Indicates that a particular name, label, or title is employed to refer to or identify a specific entity or role.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f164a9d48190b525a97b5c06ffe2 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.