Triple
T3848269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HR |
E85225
|
entity |
| Predicate | hasFormatRole |
P161
|
FINISHED |
| Object | prefix on Indian license plates |
—
|
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: prefix on Indian license plates | Statement: [HR, hasFormatRole, prefix on Indian license plates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormatRole Context triple: [HR, hasFormatRole, prefix on Indian license plates]
-
A.
hasFormatElement
Indicates that one entity includes, is composed of, or is associated with a specific structural or formatting component of its overall format.
-
B.
hasMatchFormat
Indicates that something (such as a game, event, or competition) is conducted according to a specified match format or structure.
-
C.
hasTicketFormat
Indicates that an entity’s ticket is expressed or structured in a particular format.
-
D.
hasFileFormat
Indicates that one entity (typically a digital file or resource) is encoded, stored, or represented using a specific file format defined by the other entity.
-
E.
hasRole
chosen
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcc8a0481909c35161336bdfbf9 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.