Triple
T34395447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Ignace-de-Loyola |
E882816
|
entity |
| Predicate | hasRiverineSetting |
P165
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Saint-Ignace-de-Loyola, hasRiverineSetting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverineSetting Context triple: [Saint-Ignace-de-Loyola, hasRiverineSetting, true]
-
A.
hasRiverineCharacteristic
Indicates that something possesses qualities, features, or conditions associated with rivers or river environments.
-
B.
hasRiverBedType
Indicates the type or classification of the riverbed associated with a given river or watercourse.
-
C.
hasSettlementOnRiver
Indicates that a settlement is located on or directly adjacent to a specific river.
-
D.
hasRiverInfluence
Indicates that one entity affects or is affected by a river in terms of its characteristics, behavior, or conditions.
-
E.
hasRiver
chosen
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 1, 2026, 1:59 a.m.