Triple
T30358731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida Hipólito Yrigoyen |
E772213
|
entity |
| Predicate | isNamedAfterFormerPresident |
P169107
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Avenida Hipólito Yrigoyen, isNamedAfterFormerPresident, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedAfterFormerPresident Context triple: [Avenida Hipólito Yrigoyen, isNamedAfterFormerPresident, true]
-
A.
eponymWasPresidentOf
Indicates that the person for whom something is named served as president of the specified entity (such as a country, organization, or institution).
-
B.
associatedPresident
Indicates a relationship where a person, organization, event, or entity is linked or connected to a specific president in a relevant or significant way.
-
C.
houseNamedAfter
Indicates that a house or building bears a name derived from or in honor of a particular person, place, event, or entity.
-
D.
formerPresidentOf
Indicates that one entity previously held, but no longer holds, the official position of president of another entity.
-
E.
previousPresident
Indicates that one person held the office of president immediately before another person.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682417ec08190982dd9acf7219742 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 7:57 p.m.