Triple
T35371003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siobhán Súilleabháin |
E1021766
|
entity |
| Predicate | relationshipToColm Doherty |
P206957
|
FINISHED |
| Object | sister of Colm’s former friend |
—
|
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: sister of Colm’s former friend | Statement: [Siobhán Súilleabháin, relationshipToColm Doherty, sister of Colm’s former friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToColm Doherty Context triple: [Siobhán Súilleabháin, relationshipToColm Doherty, sister of Colm’s former friend]
-
A.
relationshipTypeWithSean Maguire
Indicates the specific nature or category of relationship that an entity has with Sean Maguire.
-
B.
relationshipDynamicWithStaceyColbert
Indicates a changing or evolving interpersonal relationship involving Stacey Colbert.
-
C.
relationshipTypeWith Brian Flanagan
Indicates the specific nature or category of relationship that an entity has with Brian Flanagan.
-
D.
relationshipToCyrilHamilton
Indicates the specific familial, social, or professional relationship that an entity has to Cyril Hamilton.
-
E.
relationshipTypeWithStaceyColbert
Indicates the specific nature or category of relationship that an entity has with Stacey Colbert.
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.