Triple
T34609227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pionirska Street fire |
E888676
|
entity |
| Predicate | sentenceRelatedTo |
P179696
|
FINISHED |
| Object | Milan Lukić life imprisonment |
—
|
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: Milan Lukić life imprisonment | Statement: [Pionirska Street fire, sentenceRelatedTo, Milan Lukić life imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceRelatedTo Context triple: [Pionirska Street fire, sentenceRelatedTo, Milan Lukić life imprisonment]
-
A.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
B.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
C.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
D.
meaningIsRelatedTo
Indicates that one concept has a semantic or contextual connection to another concept without specifying the exact nature of that relationship.
-
E.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
- 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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7238172748190b8cd340ad1f4ba80 |
completed | May 3, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f72349f1108190b6a06758ab2f40bb |
completed | May 3, 2026, 10:28 a.m. |
Created at: May 1, 2026, 2:03 a.m.