Triple
T20267031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Colossal |
E498995
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Ten Words |
—
|
NE NERFINISHED |
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: Ten Words | Statement: [Super Colossal, hasPart, Ten Words]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ten Words Context triple: [Super Colossal, hasPart, Ten Words]
-
A.
Ten Words
chosen
Ten Words is a traditional English rendering of the biblical "Aseret ha-Dibrot," commonly known as the Ten Commandments given to Moses at Mount Sinai.
-
B.
Of Words
"Of Words" is a chapter in Book III that examines the nature, use, and significance of language and terminology.
-
C.
The Words
The Words is Jean-Paul Sartre’s autobiographical work in which he reflects on his childhood and the development of his literary and philosophical identity.
-
D.
The Words
The Words is a 2012 drama film about a struggling writer who achieves fame by passing off another man's manuscript as his own, exploring themes of authorship, guilt, and moral consequence.
-
E.
Fifty Words
Fifty Words is a written work by American author and playwright John Buffalo Mailer, known for exploring contemporary social and personal themes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674d001f081908910eedd262ae13a |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:42 p.m.