Triple
T26930957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Poison |
E678214
|
entity |
| Predicate | siblingDuoNickname |
P154538
|
FINISHED |
| Object | Big Poison and Little Poison |
—
|
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: Big Poison and Little Poison | Statement: [Little Poison, siblingDuoNickname, Big Poison and Little Poison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: siblingDuoNickname Context triple: [Little Poison, siblingDuoNickname, Big Poison and Little Poison]
-
A.
pairedNickname
chosen
Indicates that two entities share or are associated with a complementary or matching set of nicknames.
-
B.
nicknameOfChampionDuo
Indicates that a given nickname refers to or is used for a specific champion duo.
-
C.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
D.
childhoodNickname
Indicates that one entity is a nickname that was used to refer to the other entity during their childhood.
-
E.
hasNicknames
Indicates that an entity is known or referred to by one or more alternative informal names.
- F. None of above.
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_69eeeb4cac908190a45956c2993d1cc2 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f620497848819087881b4f82c7bc22 |
completed | May 2, 2026, 4:03 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:12 a.m.