Triple
T28136454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rank Hotels |
E714218
|
entity |
| Predicate | operatedHotelsIn |
P112111
|
FINISHED |
| Object | United Kingdom |
—
|
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: United Kingdom | Statement: [Rank Hotels, operatedHotelsIn, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedHotelsIn Context triple: [Rank Hotels, operatedHotelsIn, United Kingdom]
-
A.
hotelOperator
Indicates that an entity operates, manages, or runs a hotel as its responsible service provider or business owner.
-
B.
operatesLodgesIn
chosen
Indicates that an entity manages or runs lodging facilities located within a specified place or jurisdiction.
-
C.
hasNumberOfHotels
Indicates the quantity of hotels associated with a given entity.
-
D.
indicatedInHotelsBy
Indicates that something is highlighted, referenced, or made known within hotels by a particular source or agent.
-
E.
operatedHospitalsIn
Indicates that an entity managed or ran the operations of one or more hospitals located in a specified place or context.
- 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_69efd6af156c81908f50c2cd7db0e1ef |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fe779248c081909f0ed1a2a0df23db |
completed | May 8, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69fe76eaf6d48190998bc7168749cc42 |
completed | May 8, 2026, 11:51 p.m. |
Created at: April 27, 2026, 9:50 p.m.