Triple
T10317568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estrella de Puebla |
E242056
|
entity |
| Predicate | hasVIPCabins |
P12453
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Estrella de Puebla, hasVIPCabins, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVIPCabins Context triple: [Estrella de Puebla, hasVIPCabins, yes]
-
A.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
B.
hasCabins
chosen
Indicates that an entity possesses or includes one or more cabins as part of its structure or facilities.
-
C.
hasSleeperBerths
Indicates that an object (typically a vehicle) is equipped with one or more sleeper berths for occupants to rest or sleep.
-
D.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
E.
comfortLevelComparedToPremiumCabins
Indicates how the comfort level of something compares relative to that of premium cabins.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:49 a.m.