Triple
T9694981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Airlines Flight 175 |
E234624
|
entity |
| Predicate | impactFloorRange |
P70788
|
FINISHED |
| Object | floors 77 to 85 of the South Tower |
—
|
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: floors 77 to 85 of the South Tower | Statement: [United Airlines Flight 175, impactFloorRange, floors 77 to 85 of the South Tower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactFloorRange Context triple: [United Airlines Flight 175, impactFloorRange, floors 77 to 85 of the South Tower]
-
A.
impactFloorsApproximate
Indicates that one entity affects or influences another across an estimated or approximate number of floors or vertical levels.
-
B.
floorLevelsAffected
chosen
Indicates that certain floor levels are impacted or influenced by a specified event, condition, or action.
-
C.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
D.
floorHeight
Indicates the vertical elevation or level at which a particular floor is positioned within a structure.
-
E.
floorType
Indicates the type or material classification of a floor associated with an 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d366c488190bc153c68fef197c2 |
completed | April 1, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b9e93c8190947cce56a3925364 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:17 p.m.