Triple
T10367527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penguins of Madagascar |
E244293
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Mort |
E557439
|
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: Mort | Statement: [Penguins of Madagascar, featuresCharacter, Mort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mort Context triple: [Penguins of Madagascar, featuresCharacter, Mort]
-
A.
Mort
Mort is a comic fantasy novel in Terry Pratchett’s Discworld series that follows a young apprentice to Death himself.
-
B.
Mort
chosen
Mort is a masculine given name, often used as a short form of Morton or Mortimer.
-
C.
Morta
Morta is the Roman goddess of death and destiny, one of the three Fates who determines the moment of each mortal’s death by cutting the thread of life.
-
D.
Mortus
Mortus is the main villain of the 1995 Sega Genesis beat ’em up game Comix Zone, a demonic comic-book creator who brings his own drawings to life to battle the hero.
-
E.
Toten
Toten is a traditional rural district in eastern Norway known for its agriculture and scenic landscape, located within Innlandet county.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e96fd6f081908f630a16106996d9 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d79546b078819089dec7628c95a681 |
completed | April 9, 2026, 12:02 p.m. |
Created at: April 6, 2026, noon