Triple
T10705671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acapulco de Juárez |
E252396
|
entity |
| Predicate | populationRankInGuerrero |
P95377
|
FINISHED |
| Object | largest city in Guerrero |
—
|
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: largest city in Guerrero | Statement: [Acapulco de Juárez, populationRankInGuerrero, largest city in Guerrero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInGuerrero Context triple: [Acapulco de Juárez, populationRankInGuerrero, largest city in Guerrero]
-
A.
populationRankInMexico
Indicates the relative position of an entity in terms of population size compared to other entities within Mexico.
-
B.
populationRankInTabasco
Indicates the relative position of an entity in terms of population size compared to other entities within the region of Tabasco.
-
C.
hasPopulationRankInChile
Indicates the relative position of an entity in the ordered ranking of populations within Chile.
-
D.
strengthMexico
Indicates a relationship where some form of strength, power, or robustness is attributed to, associated with, or exerted by Mexico.
-
E.
populationRankInVenezuela
Indicates the relative position of an entity in terms of population size compared to other entities within Venezuela.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddeb060819094cd125a68070eb2 |
completed | April 9, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8ea6408190a800f9cb57372189 |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df47899481909ac0e518d94883cb |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:12 p.m.