Triple
T34945782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modlitba pro Martu |
E1007853
|
entity |
| Predicate | repopularity |
P99792
|
FINISHED |
| Object | 1989 |
—
|
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: 1989 | Statement: [Modlitba pro Martu, repopularity, 1989]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: repopularity Context triple: [Modlitba pro Martu, repopularity, 1989]
-
A.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
B.
popularityResurgence
chosen
Indicates a renewed increase in attention, favor, or widespread appeal for something after a period of decline or obscurity.
-
C.
popular
Indicates that an entity is widely liked, admired, or favored by many people compared to alternatives.
-
D.
popularityContext
Indicates the situational or domain-specific setting in which something’s popularity or level of public favor is evaluated.
-
E.
subsequentlyPopularIn
Indicates that something became popular in a particular place, group, or context after an initial point in time or after another event.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.