Triple
T10727083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mivtsa Shlomo |
E252977
|
entity |
| Predicate | recordAircraftPassengers |
P68745
|
FINISHED |
| Object | over 1100 on a single Boeing 747 |
—
|
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: over 1100 on a single Boeing 747 | Statement: [Mivtsa Shlomo, recordAircraftPassengers, over 1100 on a single Boeing 747]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordAircraftPassengers Context triple: [Mivtsa Shlomo, recordAircraftPassengers, over 1100 on a single Boeing 747]
-
A.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
B.
embarkedAircraft
Indicates that one entity boarded or got onto an aircraft as a passenger or occupant.
-
C.
aircraftRecord
chosen
Indicates a relationship where a record or entry documents information about an aircraft and its associated details.
-
D.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
-
E.
honorsNumberOfPassengersAndCrew
Indicates that the subject recognizes or commemorates the specified count of passengers and crew.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70fc7cc1c8190b4a1dcadf8563b20 |
completed | April 9, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.