Triple
T201439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza de Armas de La Serena |
E4513
|
entity |
| Predicate | hasCityRole |
P8234
|
FINISHED |
| Object | main square of La Serena |
—
|
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: main square of La Serena | Statement: [Plaza de Armas de La Serena, hasCityRole, main square of La Serena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityRole Context triple: [Plaza de Armas de La Serena, hasCityRole, main square of La Serena]
-
A.
basedInCity
Indicates that an entity has its primary location, headquarters, or main operations situated in a specified city.
-
B.
hasHomeCity
Indicates that an entity’s primary or official city of residence or affiliation is a specified city.
-
C.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
-
D.
cityRepresented
Indicates that one entity serves as the official representative or governing body for a particular city.
-
E.
hasMayor
Indicates that one entity serves as the mayor of another entity, typically a city, town, or municipality.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c2ead8481909996042efcae5e9d |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b4a0d448190a6fa6aeb30dc7e13 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25c2bda788190bcfc0bc94686f9e0 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.