Triple
T318783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America/Santiago |
E7766
|
entity |
| Predicate | hasAlternativeZoneInCountry |
P12952
|
FINISHED |
| Object | America/Punta_Arenas |
—
|
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: America/Punta_Arenas | Statement: [America/Santiago, hasAlternativeZoneInCountry, America/Punta_Arenas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeZoneInCountry Context triple: [America/Santiago, hasAlternativeZoneInCountry, America/Punta_Arenas]
-
A.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
hasRegionCode
Indicates that an entity is associated with a specific regional identifier or code.
-
C.
hasCountry
Indicates that one entity possesses, is associated with, or is located within a specific country.
-
D.
hasTimeZones
Indicates that an entity is associated with one or more time zones in which it is valid or operates.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e94513ec819089f5177f7a521e65 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eb7c56bc8190ab787801af2eec8d |
completed | Feb. 28, 2026, 1:19 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.