Triple
T33025006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arsenal de Sarandí |
E845014
|
entity |
| Predicate | notableFormerPresident |
P32134
|
FINISHED |
| Object | Julio Humberto Grondona |
E2031961
|
NE 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: Julio Humberto Grondona | Statement: [Arsenal de Sarandí, notableFormerPresident, Julio Humberto Grondona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFormerPresident Context triple: [Arsenal de Sarandí, notableFormerPresident, Julio Humberto Grondona]
-
A.
formerPresidentOf
chosen
Indicates that one entity previously held, but no longer holds, the official position of president of another entity.
-
B.
lastPresident
Indicates that one entity is the most recent individual to have held the office of president of the other entity.
-
C.
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.
-
D.
previousPresident
Indicates that one person held the office of president immediately before another person.
-
E.
notablePresidentDuring
Indicates that one entity is recognized as a notable president serving during the time period associated with another entity.
- F. None of above.
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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34e50ab1e881908c0be25cab667034 |
completed | June 19, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:23 a.m.