Triple
T20478384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muriel Pritchett |
E502382
|
entity |
| Predicate | relationshipToSarahLeary |
P140245
|
FINISHED |
| Object | romantic 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: romantic rival | Statement: [Muriel Pritchett, relationshipToSarahLeary, romantic rival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSarahLeary Context triple: [Muriel Pritchett, relationshipToSarahLeary, romantic rival]
-
A.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
B.
relationshipToLaurie
Indicates the specific type of relationship or connection that an entity has to Laurie.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
relationshipToSandraBloom
Indicates the specific type of personal or social relationship that an entity has with Sandra Bloom.
-
E.
relationshipToLaureyWilliams
Indicates the nature or type of relational connection an entity has specifically to Laurey Williams.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b54c8188190a71e35fab8d194a6 |
completed | April 20, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e5768372988190b08ef8ae67d42ab6 |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:34 a.m.