Triple
T17626242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martín de Álzaga |
E429849
|
entity |
| Predicate | yearOfArrival |
P53669
|
FINISHED |
| Object | 1770s in Buenos Aires |
—
|
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: 1770s in Buenos Aires | Statement: [Martín de Álzaga, yearOfArrival, 1770s in Buenos Aires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfArrival Context triple: [Martín de Álzaga, yearOfArrival, 1770s in Buenos Aires]
-
A.
yearOfArrivalInNewWorld
Indicates the specific year in which an entity arrived in the New World.
-
B.
historicalPeriodOfArrival
Indicates the historical time period during which an entity arrived at or first appeared in a particular place or context.
-
C.
landingYear
chosen
Indicates the year in which a landing event (such as an arrival or touchdown) took place.
-
D.
accessionYear
Indicates the calendar year in which an item, record, or entity was formally added to or registered within a collection, system, or institution.
-
E.
deploymentYear
Indicates the calendar year in which an entity (such as a system, product, or resource) was first put into active use or operation.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dbd122c8190a5db8c0088c81034 |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:52 a.m.