Triple
T10120203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Cup |
E223266
|
entity |
| Predicate | tieComposition |
P11600
|
FINISHED |
| Object | three singles and two doubles |
—
|
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: three singles and two doubles | Statement: [Thomas Cup, tieComposition, three singles and two doubles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieComposition Context triple: [Thomas Cup, tieComposition, three singles and two doubles]
-
A.
forcesComposition
Indicates that one entity compels or determines the structural makeup or arrangement of another entity.
-
B.
hornComposition
Indicates the material or substance that an entity’s horn is made of.
-
C.
branchComposition
Indicates that one branch or subdivision is structurally or functionally composed of, or made up from, another entity or set of entities.
-
D.
specialComposition
Indicates that one entity is composed of another in a distinctive or non-standard way, highlighting a particular or exceptional form of composition between them.
-
E.
partyComposition
chosen
Indicates how the members or elements of a group or party are arranged, distributed, or combined to form that party as a whole.
- 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_69ca8422047c81909d66b717b8b18cf3 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2659cdc8190b3ba91426bda55ec |
completed | April 2, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba1d360819087698d04a53cc87e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:04 p.m.