Triple
T3847501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nini |
E85207
|
entity |
| Predicate | numberInGroup |
P31691
|
FINISHED |
| Object | one of five Fuwa mascots |
—
|
LITERAL 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: one of five Fuwa mascots | Statement: [Nini, numberInGroup, one of five Fuwa mascots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberInGroup Context triple: [Nini, numberInGroup, one of five Fuwa mascots]
-
A.
numberOfGroupMembers
chosen
Indicates the total count of individual members that belong to a specified group.
-
B.
numberOfGroups
Indicates the total count of distinct groups associated with or formed within a given context or entity.
-
C.
numberInClass
Indicates that a specified entity is a member of, or belongs to, a particular class or category.
-
D.
committeeNumber
Indicates the specific numerical identifier assigned to a committee in a given context or system.
-
E.
airGroupSize
Indicates the number of units or elements grouped together in an air-related context (such as aircraft in a formation or air assets in an operation).
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcb069881909d3536b18b7802a7 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.