Triple
T15888756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BARC |
E385260
|
entity |
| Predicate | hasICBCode |
P120943
|
FINISHED |
| Object | 8355 |
—
|
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: 8355 | Statement: [BARC, hasICBCode, 8355]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasICBCode Context triple: [BARC, hasICBCode, 8355]
-
A.
hasIneCode
Indicates that an entity is associated with a specific INE (national statistics or education) code that identifies it in an official registry.
-
B.
hasICD10Code
Indicates that an entity is associated with a specific ICD-10 diagnostic code used for classifying diseases and health conditions.
-
C.
hasCodeIn
Indicates that one entity is represented, defined, or implemented within the codebase or coding context of another entity.
-
D.
ICCCode
Indicates that an entity is associated with a specific International Criminal Court (ICC) code, identifying its classification or legal reference under ICC standards.
-
E.
hasINSEECODE
Indicates that an entity is associated with a specific INSEE code, identifying it within the French national statistical and administrative system.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:51 a.m.