Triple
T36046891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Airlines Flight 553 |
E1042695
|
entity |
| Predicate | peopleOnBoard |
P94631
|
FINISHED |
| Object | 61 |
—
|
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: 61 | Statement: [United Airlines Flight 553, peopleOnBoard, 61]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peopleOnBoard Context triple: [United Airlines Flight 553, peopleOnBoard, 61]
-
A.
totalPeopleOnBoard
Indicates the total number of people currently present on a given vehicle, vessel, or similar conveyance.
-
B.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
C.
crewOnboard
Indicates that a person or group is serving as crew aboard a specific vehicle, vessel, or craft.
-
D.
crewAndPassengersCount
chosen
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
E.
hasCharacterOnboard
Indicates that a vehicle, vessel, or similar entity currently has a specific character present on board.
- 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_69f76e2e41f8819091f9fb0536920fec |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:07 p.m.