Triple
T15885087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lærdal |
E385170
|
entity |
| Predicate | fire2014Note |
P27153
|
FINISHED |
| Object | large village fire that destroyed many buildings in Lærdalsøyri |
—
|
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: large village fire that destroyed many buildings in Lærdalsøyri | Statement: [Lærdal, fire2014Note, large village fire that destroyed many buildings in Lærdalsøyri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fire2014Note Context triple: [Lærdal, fire2014Note, large village fire that destroyed many buildings in Lærdalsøyri]
-
A.
notableFire
chosen
Indicates that a significant or historically important fire event is associated with the subject.
-
B.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
C.
fireProperty
Indicates that one entity possesses or is characterized by a specific property related to fire (such as flammability, combustion behavior, or fire-related attributes).
-
D.
fireShape
Indicates that one entity has the specified geometric or visual form of a fire or flame.
-
E.
fireSymbolizes
Indicates that the concept or element of fire is used to represent, signify, or stand for another idea, quality, or meaning in a symbolic way.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.