Triple
T33855017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evey Hammond |
E867748
|
entity |
| Predicate | relationshipWithV |
P175131
|
FINISHED |
| Object | protégé |
—
|
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: protégé | Statement: [Evey Hammond, relationshipWithV, protégé]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithV Context triple: [Evey Hammond, relationshipWithV, protégé]
-
A.
relationshipType
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.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
haveRelationshipWith
chosen
Indicates that one entity is in some form of defined relationship or association with another entity.
-
E.
relationshipToBond
Indicates the specific type of personal, familial, or professional relationship an entity has to the person named Bond.
- 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_69f349943ccc8190a3c41a3e0ae46cbf |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:47 a.m.