Triple
T1951552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Airlines Flight 11 |
E42168
|
entity |
| Predicate | totalOccupants |
P2307
|
FINISHED |
| Object | 92 |
—
|
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: 92 | Statement: [American Airlines Flight 11, totalOccupants, 92]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalOccupants Context triple: [American Airlines Flight 11, totalOccupants, 92]
-
A.
hasPrimaryOccupants
Indicates that certain entities are the main or principal occupants of another entity (such as a space, structure, or location).
-
B.
userCount
Indicates the number of users associated with or involved in a given context or entity.
-
C.
hasOccupancyStatus
Indicates the current usage or availability state of something, such as whether it is occupied, vacant, or otherwise in use.
-
D.
numberOfPersons
chosen
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
E.
occupiedBy
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb34eb5748190a3ac395252951eba |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.