Triple
T1355734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Connor |
E28982
|
entity |
| Predicate | hasRelationshipType |
P10690
|
FINISHED |
| Object | professional-turned-romantic |
—
|
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: professional-turned-romantic | Statement: [Mike Connor, hasRelationshipType, professional-turned-romantic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipType Context triple: [Mike Connor, hasRelationshipType, professional-turned-romantic]
-
A.
hasCentralRelationshipType
Indicates that there exists a primary or most significant type of relationship that characterizes how two entities are related to each other.
-
B.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
hasKeyRelationship
Indicates a relationship where one entity serves as a key (e.g., identifier, access token, or primary reference) that grants access to, controls, or uniquely identifies another entity.
-
D.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
E.
hasRecordType
Indicates that an entity is associated with or classified under a specific type or category of record.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c28c8dd0819082f94c9e7c837c5f |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef7700c819099b294e8d9320e70 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.