Triple
T7374286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maracaibo |
E170084
|
entity |
| Predicate | populationRankInVenezuela |
P76633
|
FINISHED |
| Object | second-largest city |
—
|
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: second-largest city | Statement: [Maracaibo, populationRankInVenezuela, second-largest city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInVenezuela Context triple: [Maracaibo, populationRankInVenezuela, second-largest city]
-
A.
membershipStatusOfVenezuela
Indicates the membership status that Venezuela holds within a specified organization or group.
-
B.
populationRankInMexico
Indicates the relative position of an entity in terms of population size compared to other entities within Mexico.
-
C.
populationRankInVietnam
Indicates the relative position of an entity in terms of population size compared to other entities within Vietnam.
-
D.
hasPopulationRankInChile
Indicates the relative position of an entity in the ordered ranking of populations within Chile.
-
E.
populationRankInPuertoRico
Indicates the relative position of a place in terms of population size compared to other places within Puerto Rico.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a6643c81909d626c8b6a7a11fd |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0ebf9c88190af5a4d87d3fd338a |
completed | March 27, 2026, 9:04 p.m. |
Created at: March 27, 2026, 3:07 p.m.