Triple
T29562358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackbriar operation |
E750070
|
entity |
| Predicate | hasCodeNameType |
P2396
|
FINISHED |
| Object | CIA program codename |
—
|
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: CIA program codename | Statement: [Blackbriar operation, hasCodeNameType, CIA program codename]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCodeNameType Context triple: [Blackbriar operation, hasCodeNameType, CIA program codename]
-
A.
hasCodeName
Indicates that an entity is known or referred to by a particular alternative name or alias, often used for secrecy or distinction.
-
B.
hasTypeCode
Indicates that an entity is associated with a specific type classification represented by a code.
-
C.
hasCodeString
Indicates that an entity is associated with a specific code represented as a text string.
-
D.
hasTypeName
chosen
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
-
E.
hasCodenameLanguage
Indicates that a codename is expressed or defined in a particular language.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a007aa8d3a481908543f9b5d562a90c |
completed | May 10, 2026, 12:31 p.m. |
| PD | Predicate disambiguation | batch_6a007a44996481908688ccfdbc56511d |
completed | May 10, 2026, 12:29 p.m. |
Created at: April 28, 2026, 5:21 p.m.