Triple
T13011422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaos |
E322421
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Chaos |
unclear NED1
|
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: Chaos | Statement: [Chaos, title, Chaos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chaos Context triple: [Chaos, title, Chaos]
-
A.
Chaos
"Chaos" is a French film featuring Rachida Brakni in a critically acclaimed role that significantly raised her profile as an actress.
-
B.
Chaos
Chaos is the nickname of Colby Covington, an American mixed martial artist known for his outspoken persona and success in the UFC welterweight division.
-
C.
Chaos
Chaos is a powerful, water-based creature and major antagonist from the Sonic the Hedgehog series, known for transforming through the power of the Chaos Emeralds.
-
D.
Chaos
Chaos is the primordial void or yawning gap in ancient Greek cosmology, from which the first gods and elements of the universe emerged.
-
E.
Chaos
"Chaos" is a crime thriller novel in Patricia Cornwell’s Kay Scarpetta series, featuring the forensic pathologist investigating a mysterious and technologically complex death.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9e14b88190a2cee8e0c9bf31c8 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c10d5b9881909db688c1ab0e6a77 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:49 p.m.