Triple
T2807436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French colony of Saint-Domingue |
E54086
|
entity |
| Predicate | locatedOnPartOfIsland |
P3864
|
FINISHED |
| Object | western part of Hispaniola |
—
|
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: western part of Hispaniola | Statement: [French colony of Saint-Domingue, locatedOnPartOfIsland, western part of Hispaniola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedOnPartOfIsland Context triple: [French colony of Saint-Domingue, locatedOnPartOfIsland, western part of Hispaniola]
-
A.
partOfIsland
chosen
Indicates that one entity is a portion or component of an island.
-
B.
locatedInArchipelago
Indicates that one place or geographic entity is situated within or is part of a specific archipelago.
-
C.
foundOnIsland
Indicates that one entity is located or discovered on an island in relation to another entity.
-
D.
meetsInIsland
Indicates that two or more entities meet with each other at a location that is an island.
-
E.
islandOf
Indicates that one place is an island belonging to, located within, or geographically associated with another specified area or body of land/water.
- 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_69ab49dcee188190b5c6eca9ae9e3469 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde2ec2ac8190bd702ad3eafb6aed |
completed | March 7, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69abdd059f308190853191f6ffe2bc6f |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.