Triple
T27004094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IGCSE |
E680192
|
entity |
| Predicate | isInternationalCounterpartOf |
P94153
|
FINISHED |
| Object | GCSE |
—
|
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: GCSE | Statement: [IGCSE, isInternationalCounterpartOf, GCSE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInternationalCounterpartOf Context triple: [IGCSE, isInternationalCounterpartOf, GCSE]
-
A.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
B.
hasCounterpartName
Indicates that an entity has an alternative or corresponding name used as its counterpart in another context, system, or representation.
-
C.
hasCounterpartNameLanguage
Indicates that an entity’s counterpart (e.g., in another context or system) has a name expressed in a specified language.
-
D.
counterpartRelation
chosen
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
-
E.
isOppositionCounterpartOf
Indicates a relationship where one entity serves as the opposing or counterpart force, side, or position to another within a conflict, competition, or contrast.
- 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_69eeeb52908c8190bd246244686aa455 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 6:59 a.m.