Triple
T19432707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haines |
E486154
|
entity |
| Predicate | relationshipToIreland |
P135862
|
FINISHED |
| Object | visitor |
—
|
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: visitor | Statement: [Haines, relationshipToIreland, visitor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToIreland Context triple: [Haines, relationshipToIreland, visitor]
-
A.
relationshipToUK
Indicates the type or nature of a connection, association, or affiliation that an entity has with the United Kingdom.
-
B.
relationshipToIran
Indicates a specified type of relational connection or association that an entity has with Iran.
-
C.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
D.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
-
E.
relationshipToState
Indicates a relationship or connection that an entity has with a particular state or governmental body.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6335c2d7481909a44b45d95492e02 |
completed | April 20, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:37 p.m.