Triple
T34187516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Luther King Jr. Boulevard |
E877001
|
entity |
| Predicate | typicalNamingAuthority |
P205357
|
FINISHED |
| Object | city government |
—
|
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: city government | Statement: [Martin Luther King Jr. Boulevard, typicalNamingAuthority, city government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNamingAuthority Context triple: [Martin Luther King Jr. Boulevard, typicalNamingAuthority, city government]
-
A.
countryNamingAuthority
Indicates that an entity serves as the official authority responsible for assigning or approving the names of countries.
-
B.
typicalNameBearers
Indicates that the subject is a common or characteristic name borne by the entities in the object set.
-
C.
namingBasis
Indicates that one entity serves as the reason, source, or criterion for how another entity is named or designated.
-
D.
commonName
Indicates that one entity is the commonly used or vernacular name by which the other entity is known.
-
E.
designationAuthority
Indicates the entity that has the official power or responsibility to assign, grant, or confer a particular designation to 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:55 a.m.