Triple
T33423857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Ecuador earthquake |
E855916
|
entity |
| Predicate | stronglyAffectedProvince |
P84067
|
FINISHED |
| Object | Manabí Province |
—
|
NE NERFINISHED |
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: Manabí Province | Statement: [2016 Ecuador earthquake, stronglyAffectedProvince, Manabí Province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stronglyAffectedProvince Context triple: [2016 Ecuador earthquake, stronglyAffectedProvince, Manabí Province]
-
A.
affectedProvince
Indicates that a particular province is impacted or influenced by a specified event, action, or condition.
-
B.
mainAffectedProvince
chosen
Indicates the province that is primarily impacted or influenced by a given event, action, or condition.
-
C.
hasNearbyProvince
Indicates that one province is geographically close to or directly adjacent to another province.
-
D.
affectedCity
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
E.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
- F. None of above.
Provenance (3 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_69f3496fdf0081908c1aa30870ce518b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e47f37848190aadb137c81760f1f |
completed | May 3, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:36 a.m.