Triple
T7019537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smiles |
E162783
|
entity |
| Predicate | hasPartners |
P27502
|
FINISHED |
| Object | airlines |
—
|
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: airlines | Statement: [Smiles, hasPartners, airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartners Context triple: [Smiles, hasPartners, airlines]
-
A.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
B.
hasDistributionPartners
Indicates that an entity collaborates with other entities to distribute its products or services.
-
C.
hasExPartner
Indicates that one entity was formerly in a romantic or intimate partnership with another entity, but that relationship has ended.
-
D.
hasPartnerOrganization
chosen
Indicates that an entity is formally associated or collaborates with another entity as a partner organization.
-
E.
hasNetworkPartner
Indicates that an entity is connected to another entity through a formal or recognized network partnership relationship.
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:34 p.m.