Triple
T32416736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CObject |
E828347
|
entity |
| Predicate | hasMacroAssociation |
P202502
|
FINISHED |
| Object | DECLARE_DYNAMIC |
—
|
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: DECLARE_DYNAMIC | Statement: [CObject, hasMacroAssociation, DECLARE_DYNAMIC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMacroAssociation Context triple: [CObject, hasMacroAssociation, DECLARE_DYNAMIC]
-
A.
hasMacroArea
Indicates that one entity belongs to, or is located within, a broader geographic or conceptual macro-area represented by another entity.
-
B.
hasCanonicalAssociation
Indicates that one entity is formally recognized as the standard or authoritative counterpart associated with another entity.
-
C.
belongsToMacrofamily
Indicates that a language is classified as part of a larger proposed language macrofamily.
-
D.
hasMacroLanguage
Indicates that one language functions as a macrolanguage encompassing or grouping together multiple closely related individual languages or varieties.
-
E.
hasPrimaryAssociation
Indicates that one entity is chiefly or most directly connected, linked, or related to another among possible associations.
- 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_69f34919f300819092b541c6277cd68a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a008b8938608190adaccbd720111a18 |
completed | May 10, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_6a008b24baac8190baaaf50c2e9cc6bd |
completed | May 10, 2026, 1:41 p.m. |
| PDg | Predicate description generation | batch_6a008b8870b481909c1a2707a7b06d49 |
completed | May 10, 2026, 1:43 p.m. |
Created at: May 1, 2026, 12:54 a.m.