Triple
T6682321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | memorial parkway |
E152011
|
entity |
| Predicate | oftenNamedAfter |
P71722
|
FINISHED |
| Object | historical figures |
—
|
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: historical figures | Statement: [memorial parkway, oftenNamedAfter, historical figures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenNamedAfter Context triple: [memorial parkway, oftenNamedAfter, historical figures]
-
A.
oftenUsedAsNameFor
Indicates that something frequently serves as a name or designation for another entity.
-
B.
nicknamedFor
Indicates that one entity serves as the source, inspiration, or reason for another entity’s nickname.
-
C.
isNamedAfterOccupation
Indicates that an entity’s name is derived from or based on a particular occupation or profession.
-
D.
laterNamed
Indicates that an entity was given a new name at a later time, linking its original identity to its subsequent name.
-
E.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6c0a90a088190978061cb05dbe268 |
completed | March 27, 2026, 5:38 p.m. |
Created at: March 27, 2026, 2:04 p.m.