Triple
T29954220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liam Foxwell |
E760849
|
entity |
| Predicate | relationshipTypeWithFfion |
P10690
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Liam Foxwell, relationshipTypeWithFfion, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithFfion Context triple: [Liam Foxwell, relationshipTypeWithFfion, husband]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipToUser
Indicates the type of connection or association an entity has with the current user.
-
C.
relationshipTypeStart
Indicates the type or category of relationship that begins or is initiated at a specific point or event.
-
D.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
-
E.
relationshipTarget
Indicates that an entity is the object or recipient toward which a specified relationship is directed.
- 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_69f2246562b881909d57622f4086d43d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a01d48f41f4819093a5b47288a073c1 |
completed | May 11, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_6a01d3fa278c8190838174dd96ef5dde |
completed | May 11, 2026, 1:04 p.m. |
Created at: April 29, 2026, 6:26 p.m.