Triple
T2606704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léogâne |
E58676
|
entity |
| Predicate | percentageDestroyed2010Earthquake |
P41204
|
FINISHED |
| Object | over 80 percent of buildings |
—
|
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: over 80 percent of buildings | Statement: [Léogâne, percentageDestroyed2010Earthquake, over 80 percent of buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageDestroyed2010Earthquake Context triple: [Léogâne, percentageDestroyed2010Earthquake, over 80 percent of buildings]
-
A.
percentageOfWorldEarthquakes
Indicates the proportion of all earthquakes worldwide that occur in or are attributed to a specific entity or region.
-
B.
earthquakeMagnitude
Indicates the measured strength or intensity of an earthquake, typically expressed on a standardized magnitude scale.
-
C.
notableEarthquake
Indicates that an earthquake event is significant or noteworthy due to its magnitude, impact, or historical importance.
-
D.
earthquakeType
Indicates the specific classification or category of an earthquake based on its characteristics or cause.
-
E.
relatedEarthquakeZone
Indicates that one entity is geographically or geologically associated with a particular earthquake-prone zone or seismic region.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8dd05c48190b4f90031642c4091 |
completed | March 7, 2026, 7:50 a.m. |
Created at: March 6, 2026, 9:49 p.m.