Triple
T5420783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thing 1 |
E121242
|
entity |
| Predicate | partnerInMischief |
P21638
|
FINISHED |
| Object | Thing 2 |
E123910
|
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: Thing 2 | Statement: [Thing 1, partnerInMischief, Thing 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thing 2 Context triple: [Thing 1, partnerInMischief, Thing 2]
-
A.
Thing 2
chosen
Thing 2 is a mischievous, blue-haired character from Dr. Seuss's "The Cat in the Hat," known for causing playful chaos alongside Thing 1.
-
B.
Thing 1
Thing 1 is a mischievous, energetic character from Dr. Seuss's "The Cat in the Hat," known for causing playful chaos alongside Thing 2.
-
C.
The Toy
The Toy is a 1982 comedy film starring Richard Pryor as a man hired by a wealthy businessman to be a spoiled rich child's "live" plaything, exploring themes of race, class, and exploitation through slapstick humor.
-
D.
The Peg
The Peg is a colloquial nickname for Winnipeg, the capital and largest city of the Canadian province of Manitoba.
-
E.
The Third Twin
The Third Twin is a techno-thriller novel by Ken Follett that centers on genetic engineering, secret experiments, and a deadly conspiracy uncovered through DNA research.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91ae18cc8190aefe610f91b5382c |
completed | March 20, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf4123bab881908379e7612d5b39b9 |
completed | March 22, 2026, 1:08 a.m. |
Created at: March 20, 2026, 2:06 p.m.