Triple
T15333050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimball |
E366588
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | KIM |
E1020244
|
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: KIM | Statement: [Kimball, hasStationCode, KIM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KIM Context triple: [Kimball, hasStationCode, KIM]
-
A.
KIM
chosen
KIM is the IATA airport code for Kimberley Airport, a regional airport serving the city of Kimberley in South Africa.
-
B.
Kiyanu Kim
Kiyanu Kim is a songwriter and producer best known for co-writing Miley Cyrus's hit single "Wrecking Ball."
-
C.
Na Kim
Na Kim is a contemporary book cover designer and artist known for her bold, minimalist, and concept-driven visual work.
-
D.
Chin-kim
Chin-kim, also known as Zhenjin, was a Yuan dynasty imperial prince and the designated heir of Kublai Khan in 13th-century Mongolia-China.
-
E.
Kim
Kim is a supporting character in the psychological horror film "It Comes at Night," involved in the tense, paranoia-driven dynamics between two families during a mysterious apocalyptic outbreak.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01ecb904819082454622dcd77556 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.