Triple
T12282938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campeonato AFP PlanVital |
E292757
|
entity |
| Predicate | organizer |
P123
|
FINISHED |
| Object | ANFP |
E59992
|
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: ANFP | Statement: [Campeonato AFP PlanVital, organizer, ANFP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ANFP Context triple: [Campeonato AFP PlanVital, organizer, ANFP]
-
A.
ANFP
chosen
ANFP is the National Professional Football Association that organizes and regulates professional football competitions in Chile.
-
B.
ANF
ANF is a French rolling stock manufacturer known for producing various types of railway vehicles and equipment.
-
C.
ANP
ANP is the national police force of Afghanistan responsible for law enforcement, public order, and internal security across the country.
-
D.
ANA
ANA is the Portuguese company responsible for managing and operating the main airports in Portugal.
-
E.
ANA
ANA is the commonly used abbreviation for the Afghan National Army, the former main land warfare branch of Afghanistan’s armed forces.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cf2b09c81908a11581d33f65be0 |
completed | April 10, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63464486c819085452675a43785b1 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:52 p.m.