Triple
T38212852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abby Holland |
E1010601
|
entity |
| Predicate | relationshipTypeWithHarper Caldwell |
P204543
|
FINISHED |
| Object | girlfriend |
—
|
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: girlfriend | Statement: [Abby Holland, relationshipTypeWithHarper Caldwell, girlfriend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithHarper Caldwell Context triple: [Abby Holland, relationshipTypeWithHarper Caldwell, girlfriend]
-
A.
relationshipTypeWithCharlie Harper
Indicates the specific nature or category of relationship that an entity has with Charlie Harper.
-
B.
relationshipTypeWithDylanHarper
Indicates the specific nature or category of relationship that an entity has with Dylan Harper.
-
C.
relationshipWithAlanHarper
Indicates that one entity has a specified type of personal or social relationship with Alan Harper.
-
D.
relationshipTypeWithLorelai
Indicates the specific nature or category of relationship that an entity has with Lorelai.
-
E.
relationshipWithHarold
Indicates that an entity has some form of personal, social, or professional relationship with Harold.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.