Triple
T7568274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tzcode |
E179174
|
entity |
| Predicate | archiveFormat |
P77649
|
FINISHED |
| Object | tar.gz |
—
|
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: tar.gz | Statement: [tzcode, archiveFormat, tar.gz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: archiveFormat Context triple: [tzcode, archiveFormat, tar.gz]
-
A.
archiveType
Indicates the classification or category assigned to an archive within a system or collection.
-
B.
archiveContent
Indicates that content is being stored or moved into an archive state for long-term retention or historical reference.
-
C.
archivesType
Indicates that one entity serves as an archival record or stored version of another entity, specifying the type or category of that archived content.
-
D.
archiveSource
Indicates that one entity serves as the originating source or provider of materials or data that are stored or preserved in an archive associated with another entity.
-
E.
archivesModel
Indicates that one entity stores and preserves another entity as an archived model for long-term reference or retrieval.
- 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_69c69f316e50819081a271c85c06f918 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f91d9bfc8190af6f5f8211c3dda2 |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f59517648190ac0a9e9cba045dd5 |
completed | March 27, 2026, 9:24 p.m. |
Created at: March 27, 2026, 3:51 p.m.