Triple
T186131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law Regarding the National Flag and National Anthem |
E3983
|
entity |
| Predicate | hasLegalNumber |
P1117
|
FINISHED |
| Object | 127 |
—
|
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: 127 | Statement: [Law Regarding the National Flag and National Anthem, hasLegalNumber, 127]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalNumber Context triple: [Law Regarding the National Flag and National Anthem, hasLegalNumber, 127]
-
A.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
B.
publicLawNumber
chosen
Indicates the specific public law identifier associated with a legislative act or statute.
-
C.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
D.
hasNumberCategory
Indicates that an entity is associated with a specific numerical classification or type.
-
E.
hasNumberOfLetters
Indicates a relationship where an entity is associated with the count of letters it contains.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.