Triple
T17068372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Bang (System 6 codename) |
E414147
|
entity |
| Predicate | codenameScope |
P125732
|
FINISHED |
| Object | subset of System 6 versions |
—
|
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: subset of System 6 versions | Statement: [Big Bang (System 6 codename), codenameScope, subset of System 6 versions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codenameScope Context triple: [Big Bang (System 6 codename), codenameScope, subset of System 6 versions]
-
A.
codenameContext
Indicates that an entity is associated with or used as a codename within a particular contextual scope or situation.
-
B.
codenameComponent
Indicates that one entity serves as the codename or code-designation assigned to another entity as its component or identifying label.
-
C.
codenameOwner
Indicates that one entity is the designated owner or holder of the specified codename associated with another entity.
-
D.
encodingScope
Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
-
E.
codenameFormat
Indicates that an entity’s codename follows a specific prescribed format or pattern.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbbeb2a48190a733a4cc829c16de |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.