Triple
T28467233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Martin Luther King Jr. Expressway |
E720325
|
entity |
| Predicate | hasCommemoratedPersonBirthYear |
P21141
|
FINISHED |
| Object | 1929 |
—
|
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: 1929 | Statement: [Dr. Martin Luther King Jr. Expressway, hasCommemoratedPersonBirthYear, 1929]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommemoratedPersonBirthYear Context triple: [Dr. Martin Luther King Jr. Expressway, hasCommemoratedPersonBirthYear, 1929]
-
A.
commemoratesPersonBirthYear
chosen
Indicates that something is intended to honor or mark the year in which a specific person was born.
-
B.
commemoratedYear
Indicates the specific year in which an event, person, or entity is formally remembered, honored, or celebrated.
-
C.
hasCenturyOfPersonCommemorated
Indicates the century in which the person being commemorated lived or was active.
-
D.
numberOfCommemoratedPersons
Indicates the count of distinct persons who are commemorated or honored in a given context or entity.
-
E.
hasYearOfNamesakeEvent
Indicates the specific year in which the event that a namesake is based on or named after took place.
- 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_69f01a58a67c819097936d9e8da8d6e6 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69ffab5adf2c819084700c5ea34615bf |
completed | May 9, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69ffaabffa208190b5214ca17cc8a5ea |
completed | May 9, 2026, 9:44 p.m. |
Created at: April 28, 2026, 2:45 a.m.