Triple
T34238495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rub' al Khali crossing 1930 |
E878396
|
entity |
| Predicate | hasArrivalPoint |
P131665
|
FINISHED |
| Object | Doha |
—
|
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: Doha | Statement: [Rub' al Khali crossing 1930, hasArrivalPoint, Doha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArrivalPoint Context triple: [Rub' al Khali crossing 1930, hasArrivalPoint, Doha]
-
A.
hasArrivalArea
Indicates that an entity is associated with a specific area designated for arrivals, such as where incoming people or items first enter or are received.
-
B.
isMainArrivalPointFor
chosen
Indicates that a location serves as the primary arrival point for a given entity or flow of entities.
-
C.
hasArrivalLevel
Indicates that an entity arrives at or is associated with a specific level, floor, or tier within a larger structure or system.
-
D.
hasArrivalAirport
Indicates the airport at which a journey, flight, or trip concludes or arrives.
-
E.
arrivalFrom
Indicates that an entity arrives at a location or state originating from a specified source location or state.
- 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_69f349b22d8c819096b22df268382aa9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
Created at: May 1, 2026, 1:56 a.m.