Triple
T1904541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic Day (Iraq) |
E37769
|
entity |
| Predicate | hasOfficialCharacter |
P33820
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Republic Day (Iraq), hasOfficialCharacter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialCharacter Context triple: [Republic Day (Iraq), hasOfficialCharacter, yes]
-
A.
hasOfficial
Indicates that an entity is formally associated with, represented by, or served by a designated official or office-holder.
-
B.
areOfficialIn
Indicates that an entity holds an official role, position, or capacity within another entity (such as an organization, institution, or jurisdiction).
-
C.
hasIconicCharacter
Indicates that something is associated with a character widely recognized as emblematic or highly representative of it.
-
D.
hasNotableFictionalBearer
Indicates that an entity is associated with at least one well-known fictional character that bears its name or designation.
-
E.
hasMermaidCharacter
Indicates that an entity includes, features, or is associated with a character who is a mermaid.
- 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafe9f8b0819086d8f6288511c66d |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb34c4a64819096e12b152b84c334 |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:35 p.m.