Triple
T76501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America/Bogota |
E1527
|
entity |
| Predicate | isCanonicalZone |
P4818
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [America/Bogota, isCanonicalZone, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCanonicalZone Context triple: [America/Bogota, isCanonicalZone, true]
-
A.
hasTimeZones
Indicates that an entity is associated with one or more time zones in which it is valid or operates.
-
B.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
-
C.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
D.
locatedInTimeZone
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
-
E.
isTwoLetterCode
Indicates that something functions as a two-letter abbreviated code representing a larger name or concept.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a25597b6c48190849c3e9e6351b983 |
completed | Feb. 28, 2026, 2:40 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.