Triple
T36836695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milot, Haiti |
E910289
|
entity |
| Predicate | hasNearbyMountainFortress |
P66389
|
FINISHED |
| Object | Citadelle Laferrière |
—
|
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: Citadelle Laferrière | Statement: [Milot, Haiti, hasNearbyMountainFortress, Citadelle Laferrière]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMountainFortress Context triple: [Milot, Haiti, hasNearbyMountainFortress, Citadelle Laferrière]
-
A.
containsFortress
Indicates that a location or area includes a fortress within its boundaries.
-
B.
hasFortificationNearby
chosen
Indicates that one entity is located in proximity to, or within the immediate area of, a fortification structure associated with it.
-
C.
hasFortificationsFrom
Indicates that an entity possesses or is protected by fortifications that originate from or were constructed by another specified source or period.
-
D.
hasNearbyMilitaryTown
Indicates that one location is situated close to a town whose primary function or identity is associated with military presence or activity.
-
E.
hasFortressConstructed
Indicates that a fortress has been built or established for, by, or at the associated entity.
- 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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a006fe981488190b4287289a3327664 |
completed | May 10, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_6a006f6976ec8190ba2c04fbaa946345 |
completed | May 10, 2026, 11:43 a.m. |
Created at: May 3, 2026, 4:13 p.m.