Triple
T1124669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margo Channing |
E24691
|
entity |
| Predicate | relationshipToEveHarrington |
P25236
|
FINISHED |
| Object | mentor-turned-rival |
—
|
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: mentor-turned-rival | Statement: [Margo Channing, relationshipToEveHarrington, mentor-turned-rival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEveHarrington Context triple: [Margo Channing, relationshipToEveHarrington, mentor-turned-rival]
-
A.
relationshipToLaureyWilliams
Indicates the nature or type of relational connection an entity has specifically to Laurey Williams.
-
B.
relationToProvidence
Indicates a relationship or connection that something or someone has to Providence, such as origin, location, affiliation, or relevance.
-
C.
relationshipToAuntEller
Indicates the specific familial relationship that an entity has to Aunt Eller (e.g., whether and how they are related to her).
-
D.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:44 p.m.