Triple
T17343342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AF4590 |
E421118
|
entity |
| Predicate | impactWith |
P33468
|
FINISHED |
| Object | hotel in Gonesse |
—
|
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: hotel in Gonesse | Statement: [AF4590, impactWith, hotel in Gonesse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactWith Context triple: [AF4590, impactWith, hotel in Gonesse]
-
A.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
B.
impactBuilding
chosen
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
C.
impactOnSubject
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
-
D.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
E.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a18aca88190a816da85dd5fe371 |
completed | April 19, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.