Triple
T17185049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Nuns and a Pack Mule |
E417082
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | “Marmoset” |
E417087
|
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: “Marmoset” | Statement: [Two Nuns and a Pack Mule, hasPart, “Marmoset”]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: “Marmoset” Context triple: [Two Nuns and a Pack Mule, hasPart, “Marmoset”]
-
A.
Marmoset
chosen
"Marmoset" is a song by the American noise rock band Rapeman, known for its abrasive sound and association with the late-1980s underground rock scene.
-
B.
Pigmy
"Pigmy" is a funk and soul track by Booker T. & the M.G.'s from their 1967 album *Hip Hug-Her*.
-
C.
Macaca
Macaca is a diverse genus of Old World monkeys that includes numerous macaque species widely distributed across Asia and parts of North Africa.
-
D.
Moppet
Moppet is one of the mischievous kitten siblings in Beatrix Potter’s children’s story "The Tale of Tom Kitten."
-
E.
"Love Monkey"
"Love Monkey" is a short-lived 2006 American dramedy television series about a music executive navigating his personal and professional life, starring Tom Cavanagh.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42d9556c881908ccaee4ef77dbe1f |
completed | April 19, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fcc424081908a7e74df0523443e |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:37 a.m.