Triple
T27458696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BR-10 |
E692671
|
entity |
| Predicate | hasCodePrefixMeaning |
P75846
|
FINISHED |
| Object | BR denotes the state of Bihar |
—
|
NE NERFINISHED |
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: BR denotes the state of Bihar | Statement: [BR-10, hasCodePrefixMeaning, BR denotes the state of Bihar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCodePrefixMeaning Context triple: [BR-10, hasCodePrefixMeaning, BR denotes the state of Bihar]
-
A.
hasPrefixMeaning
Indicates that one entity serves as a semantic prefix of another, contributing a specific meaning to the start of the second entity.
-
B.
hasStationCodePrefix
chosen
Indicates that one entity’s station code begins with the prefix specified by the other entity.
-
C.
hasCodeString
Indicates that an entity is associated with a specific code represented as a text string.
-
D.
hasCodeIn
Indicates that one entity is represented, defined, or implemented within the codebase or coding context of another entity.
-
E.
tailCodePrefix
Indicates that one entity’s tail code begins with, or is prefixed by, the string represented by the other 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
Created at: April 27, 2026, 12:49 p.m.