Triple
T15296825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hansel McDonald |
E365681
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Mugatu |
E372945
|
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: Mugatu | Statement: [Hansel McDonald, associatedWith, Mugatu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mugatu Context triple: [Hansel McDonald, associatedWith, Mugatu]
-
A.
Mugatu
chosen
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
-
B.
Mungava
Mungava is an alternative name for Bellona Island, a small inhabited island in the Solomon Islands in the South Pacific.
-
C.
Mogareeka
Mogareeka is a small coastal locality in New South Wales, Australia, known for its beaches and estuarine scenery near Tathra.
-
D.
Mungaka
Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
-
E.
Morungaba
Morungaba is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and integration into the economically significant Campinas metropolitan area.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e036848c1881908fbaaae0216d6d27 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef89bb46481908f27fa98eb6ac5c3 |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:15 a.m.