Triple
T25223336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quincy McCall |
E632020
|
entity |
| Predicate | relationshipTypeWithMonicaWright |
P180475
|
FINISHED |
| Object | childhood friends to lovers |
—
|
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: childhood friends to lovers | Statement: [Quincy McCall, relationshipTypeWithMonicaWright, childhood friends to lovers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithMonicaWright Context triple: [Quincy McCall, relationshipTypeWithMonicaWright, childhood friends to lovers]
-
A.
relationshipTypeWith Mona Stangley
Indicates the specific type or nature of relationship that an entity has with Mona Stangley.
-
B.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
C.
relationshipTypeWith Alicia Johns
Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
-
D.
relationshipToNicole
Indicates the specific type of relationship or connection that an entity has with Nicole.
-
E.
relationshipTypeWithNickWells
Indicates the specific nature or category of relationship that an entity has with Nick Wells.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 21, 2026, 1:03 p.m.