Triple
T37939000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vila Velha |
E946429
|
entity |
| Predicate | stateRankByPopulation |
P21163
|
FINISHED |
| Object | one of the most populous cities in Espírito Santo |
—
|
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: one of the most populous cities in Espírito Santo | Statement: [Vila Velha, stateRankByPopulation, one of the most populous cities in Espírito Santo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateRankByPopulation Context triple: [Vila Velha, stateRankByPopulation, one of the most populous cities in Espírito Santo]
-
A.
stateRank
chosen
Indicates the relative position or standing of an entity within a specific state-level ordering or hierarchy.
-
B.
rankByPopulationInUS
Indicates the relative ordering of entities based on the size of their populations within the United States.
-
C.
rankByPopulationInUnitedStates
Indicates the relative ordering of entities based on their population size within the United States.
-
D.
provinceRank
Indicates the relative position or level assigned to a province within an ordered ranking or hierarchy.
-
E.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ff109695008190a22b47ef8be2e3f9 |
completed | May 9, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69ff0f243ea88190970d2c520b55c816 |
completed | May 9, 2026, 10:40 a.m. |
Created at: May 3, 2026, 4:20 p.m.