Triple
T11765128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipal Securities Rulemaking Board |
E279763
|
entity |
| Predicate | EMMAIs |
P101473
|
FINISHED |
| Object | online disclosure system for municipal securities |
—
|
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: online disclosure system for municipal securities | Statement: [Municipal Securities Rulemaking Board, EMMAIs, online disclosure system for municipal securities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EMMAIs Context triple: [Municipal Securities Rulemaking Board, EMMAIs, online disclosure system for municipal securities]
-
A.
HamIs
Indicates that one entity is identified, classified, or equated as ham in relation to another entity.
-
B.
الأم
Indicates a maternal relationship where one entity is the mother of another entity.
-
C.
eve
Indicates a relationship where one entity is the evening or night-time counterpart, phase, or occurrence associated with another entity.
-
D.
HethIs
Indicates that one entity is identified as or equated with another entity, expressing a basic “is” or “being” relationship between them.
-
E.
MacMeans
Indicates that one entity serves as the meaning, definition, or semantic interpretation of another entity.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
| PDg | Predicate description generation | batch_69d8a8c07d648190b8650d31f3a15090 |
completed | April 10, 2026, 7:37 a.m. |
Created at: April 8, 2026, 9:41 p.m.