Triple
T14163494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyderabad International Convention Centre |
E351007
|
entity |
| Predicate | hasOnsiteHotelRooms |
P84196
|
FINISHED |
| Object | 288 |
—
|
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: 288 | Statement: [Hyderabad International Convention Centre, hasOnsiteHotelRooms, 288]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnsiteHotelRooms Context triple: [Hyderabad International Convention Centre, hasOnsiteHotelRooms, 288]
-
A.
hasHotelsOnSite
chosen
Indicates that the subject location includes one or more hotels situated directly on its premises.
-
B.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
C.
numberOfHotelRooms
Indicates the total count of rooms that a given hotel has.
-
D.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
E.
hasPeriodRooms
Indicates that an entity contains rooms that are decorated or preserved to reflect specific historical periods.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de613a4a2081908fd51bf4b4d82b6c |
completed | April 14, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:59 a.m.