Triple
T28814851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Patrick's Society of Buenos Aires |
E727613
|
entity |
| Predicate | hasNetworkWith |
P8946
|
FINISHED |
| Object | Irish community organizations in Argentina |
—
|
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: Irish community organizations in Argentina | Statement: [St. Patrick's Society of Buenos Aires, hasNetworkWith, Irish community organizations in Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNetworkWith Context triple: [St. Patrick's Society of Buenos Aires, hasNetworkWith, Irish community organizations in Argentina]
-
A.
hasNet
Indicates that one entity possesses, is equipped with, or includes a net.
-
B.
hasPrimaryNetwork
Indicates that an entity is associated with or connected to its main or most important network among potentially multiple networks.
-
C.
hasNetworkName
Indicates that an entity is associated with a specific network identifier or name.
-
D.
hasNetworkOfOrigin
Indicates that an entity originates from, or is primarily associated with, a particular network or source network.
-
E.
hasNetworkPartner
chosen
Indicates that an entity is connected to another entity through a formal or recognized network partnership relationship.
- 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_69f0319d09088190bbf14cdf1987792a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: April 28, 2026, 6:32 a.m.