Triple
T33425293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | selección femenina de fútbol de Ecuador |
E855958
|
entity |
| Predicate | ciudadSedeFrecuente |
P142915
|
FINISHED |
| Object | Quito |
—
|
NE NERFINISHED |
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: Quito | Statement: [selección femenina de fútbol de Ecuador, ciudadSedeFrecuente, Quito]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ciudadSedeFrecuente Context triple: [selección femenina de fútbol de Ecuador, ciudadSedeFrecuente, Quito]
-
A.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
-
B.
usedCity
chosen
Indicates that an entity made use of or operated within a particular city as part of its activities or functions.
-
C.
isMostFrequentlyVisitedRegionOf
Indicates that a region is the one visited most often by a particular entity compared to all other regions.
-
D.
clubCity
Indicates that a club is based in or associated with a particular city.
-
E.
nativeCity
Indicates that a city is the place where a person was born or is originally from.
- 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_69f3496fdf0081908c1aa30870ce518b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e47f37848190aadb137c81760f1f |
completed | May 3, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:36 a.m.