Triple
T20511332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CO-ANT |
E503568
|
entity |
| Predicate | appliesTo |
P1129
|
FINISHED |
| Object | Itagüí |
—
|
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: Itagüí | Statement: [CO-ANT, appliesTo, Itagüí]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itagüí Context triple: [CO-ANT, appliesTo, Itagüí]
-
A.
Itagüí
chosen
Itagüí is a densely populated industrial and commercial city in northwestern Colombia, located in the metropolitan area of Medellín.
-
B.
Kurume
Kurume is a mid-sized city in southwestern Japan known for its traditional textile industry, ramen culture, and location along the Chikugo River in Fukuoka Prefecture.
-
C.
Minoh
Minoh is a suburban city in northern Osaka Prefecture, Japan, known for its scenic Minoh Waterfall, autumn foliage, and residential communities.
-
D.
Toda City
Toda City is a municipality in Saitama Prefecture, Japan, located just north of Tokyo and known as a residential and commuter town within the Greater Tokyo metropolitan area.
-
E.
Ōta City
Ōta City is a special ward in southern Tokyo, Japan, known for Haneda Airport, its coastal location on Tokyo Bay, and a mix of residential, industrial, and commercial districts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dcb8f5c8190b0d4c09f3669a8ec |
completed | April 20, 2026, 9:42 p.m. |
Created at: April 16, 2026, 11:36 a.m.