Triple
T24294799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qibla (toward the Kaaba) |
E605927
|
entity |
| Predicate | indicatedInHotelsBy |
P155430
|
FINISHED |
| Object | Qibla arrow in rooms |
—
|
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: Qibla arrow in rooms | Statement: [Qibla (toward the Kaaba), indicatedInHotelsBy, Qibla arrow in rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indicatedInHotelsBy Context triple: [Qibla (toward the Kaaba), indicatedInHotelsBy, Qibla arrow in rooms]
-
A.
isResortDestinationFor
Indicates that a place serves as a resort destination specifically intended for or frequented by a particular person, group, or entity.
-
B.
locatedInHotelCategory
Indicates that one entity is situated within, or belongs to, a specific category or classification of hotels.
-
C.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
D.
notableHotel
Indicates that a hotel is notable or significant in some recognized way, such as historical, cultural, or commercial importance.
-
E.
hasNumberOfHotels
Indicates the quantity of hotels associated with a given entity.
- F. None of above. chosen
Provenance (4 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f291593c0881908a6827f0d8899fe6 |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:09 a.m.