Triple
T9694992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Airlines Flight 175 |
E234624
|
entity |
| Predicate | sequenceInAttacks |
P89670
|
FINISHED |
| Object | second plane to hit the World Trade Center |
—
|
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: second plane to hit the World Trade Center | Statement: [United Airlines Flight 175, sequenceInAttacks, second plane to hit the World Trade Center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sequenceInAttacks Context triple: [United Airlines Flight 175, sequenceInAttacks, second plane to hit the World Trade Center]
-
A.
numberOfAttacks
Indicates the count of distinct attack events associated with a given entity or interaction.
-
B.
sequenceInGames
Indicates that one game or event occurs as part of an ordered sequence within a series of games.
-
C.
notableAttack
Indicates that an entity carried out, was involved in, or is strongly associated with a particularly significant or well-known attack.
-
D.
attackedIn
Indicates that one entity carried out an attack in the location, context, or time frame specified by another entity or value.
-
E.
attackType
Indicates the specific method, style, or category of attack used in an aggressive or hostile action between entities.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69ccd9408c848190b84dd74d87f76273 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:17 p.m.