Triple
T18797594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Chueco |
E459676
|
entity |
| Predicate | appliedToPersonNationality |
P18680
|
FINISHED |
| Object | Argentine |
—
|
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: Argentine | Statement: [El Chueco, appliedToPersonNationality, Argentine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToPersonNationality Context triple: [El Chueco, appliedToPersonNationality, Argentine]
-
A.
appliesToPersonNationality
chosen
Indicates that something is relevant or applicable specifically to a person’s nationality.
-
B.
basedOnNationality
Indicates a relationship where something is determined, derived, or decided according to a person’s nationality.
-
C.
hasParticipantNationality
Indicates that a participant in an event, activity, or relation has a specific nationality.
-
D.
includedNationality
Indicates that one entity’s set of nationalities contains or encompasses the nationality of another entity.
-
E.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a020821881909749f6a1c6cd195b |
completed | April 20, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.