Triple
T13860638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guy Gardner |
E333184
|
entity |
| Predicate | closeAlly |
P14992
|
FINISHED |
| Object | Kilowog |
E447846
|
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: Kilowog | Statement: [Guy Gardner, closeAlly, Kilowog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kilowog Context triple: [Guy Gardner, closeAlly, Kilowog]
-
A.
Kilowog
chosen
Kilowog is a powerful alien member of the Green Lantern Corps, best known as the gruff but loyal drill instructor who trains new Green Lanterns.
-
B.
Boontling
Boontling is a highly localized and inventive American English argot developed in the late 19th century in Boonville, California, known for its unique vocabulary and obscure origins.
-
C.
Bekwarra
Bekwarra is a notable town and local government area in southeastern Nigeria, recognized for its predominantly agrarian community and cultural heritage within Cross River State.
-
D.
Bugaloo
Bugaloo is a minor character in the 1994 basketball-themed drama film "Above the Rim."
-
E.
Kikisoblu
Kikisoblu, better known as Princess Angeline, was the eldest daughter of Chief Seattle and a notable Duwamish woman who became a symbolic figure in early Seattle history.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02de38e48190b6ead95561031c32 |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0fd3ffc8190965a730843411b80 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.