Triple
T22837895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Díaz |
E565994
|
entity |
| Predicate | hasFrequencyRankInSpain |
P39630
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Díaz, hasFrequencyRankInSpain, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequencyRankInSpain Context triple: [Díaz, hasFrequencyRankInSpain, high]
-
A.
frequencyCategoryInSpain
chosen
Indicates the categorized level of how often something occurs or is observed within Spain.
-
B.
populationRankInCommunityOfMadrid
Indicates the relative position of an entity in terms of population size compared to other entities within the Community of Madrid.
-
C.
statusInSpain
Indicates the legal, social, or official condition or standing that an entity has within the jurisdiction of Spain.
-
D.
populationRankInValencianCommunity
Indicates the relative position of an entity in terms of population size compared to other entities within the Valencian Community.
-
E.
hasFrequencyRankInEngland
Indicates that an entity (such as a name or term) has a specific position in a ranked list based on how frequently it occurs in England.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e8244dc819089c0a7525fb512ab |
completed | April 29, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:35 p.m.