Triple
T6876371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 Haiti earthquake |
E158680
|
entity |
| Predicate | epicenterDistanceFromPort-au-Prince |
P28710
|
FINISHED |
| Object | about 25 km west |
—
|
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: about 25 km west | Statement: [2010 Haiti earthquake, epicenterDistanceFromPort-au-Prince, about 25 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epicenterDistanceFromPort-au-Prince Context triple: [2010 Haiti earthquake, epicenterDistanceFromPort-au-Prince, about 25 km west]
-
A.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
-
B.
distanceFromHypocenter
chosen
Indicates the measured distance between a specified location and the hypocenter (origin point) of an event such as an earthquake.
-
C.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
D.
epicenter
Indicates the central point or focal location from which an event, influence, or effect originates or is most intensely experienced.
-
E.
distanceFromCayenne
Indicates the measured distance between a given entity or location and the place named Cayenne.
- 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_69c68832af1481908ce356e133ebaebe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8cb76108190a5136240ed85d900 |
completed | March 27, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b363dc8190a7225b540ab2bc40 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:22 p.m.