Triple
T17334353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XP (Flying Blue) |
E420895
|
entity |
| Predicate | statusValidityLinkedTo |
P45754
|
FINISHED |
| Object | XP earned in the qualification period |
—
|
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: XP earned in the qualification period | Statement: [XP (Flying Blue), statusValidityLinkedTo, XP earned in the qualification period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusValidityLinkedTo Context triple: [XP (Flying Blue), statusValidityLinkedTo, XP earned in the qualification period]
-
A.
statusIndicates
Indicates that a particular status value conveys or reflects the current condition, state, or situation of an entity or process.
-
B.
statusIncludes
Indicates that one entity’s status set contains or encompasses the status (or statuses) of another entity.
-
C.
identityStatus
Indicates the current state or condition of an entity’s identity, such as whether it is verified, active, pending, or otherwise classified.
-
D.
associatedStatus
chosen
Indicates that one entity is linked to or characterized by a particular status or condition.
-
E.
statusModel
Indicates that an entity is associated with a particular status representation or status-handling model.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a106df48190a50f96febc13cde7 |
completed | April 19, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:43 a.m.