Triple
T21654863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Whittlesey |
E534432
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Lauren Whittlesey
Lauren Whittlesey is the daughter of Diane Whittlesey, a character from the television series "Oz."
|
E1546611
|
NE FINISHED |
How this triple was built (4 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: Lauren Whittlesey | Statement: [Diane Whittlesey, hasChild, Lauren Whittlesey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Whittlesey Context triple: [Diane Whittlesey, hasChild, Lauren Whittlesey]
-
A.
Lauren Poultney
Lauren Poultney is a senior British police officer who serves as the Chief Constable of South Yorkshire Police.
-
B.
Lauren Reynolds
Lauren Reynolds is a central character in the 2013 indie drama film "Breathe In," portrayed as a young woman whose arrival disrupts the emotional equilibrium of a suburban family.
-
C.
Lauren Reynolds
Lauren Reynolds is a character in the romantic comedy film "Blended," which stars Adam Sandler and Drew Barrymore.
-
D.
Lauren Greer
Lauren Greer is a notable individual recognized for achievements significant enough to be associated with the surname Greer.
-
E.
Lauren McCauley
Lauren McCauley is a character in the crime drama series "Black Bird," involved in the story surrounding the investigation and psychological dynamics of the case.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lauren Whittlesey Triple: [Diane Whittlesey, hasChild, Lauren Whittlesey]
Generated description
Lauren Whittlesey is the daughter of Diane Whittlesey, a character from the television series "Oz."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauren Whittlesey Target entity description: Lauren Whittlesey is the daughter of Diane Whittlesey, a character from the television series "Oz."
-
A.
Lauren Poultney
Lauren Poultney is a senior British police officer who serves as the Chief Constable of South Yorkshire Police.
-
B.
Lauren Reynolds
Lauren Reynolds is a character in the romantic comedy film "Blended," which stars Adam Sandler and Drew Barrymore.
-
C.
Lauren Reynolds
Lauren Reynolds is a central character in the 2013 indie drama film "Breathe In," portrayed as a young woman whose arrival disrupts the emotional equilibrium of a suburban family.
-
D.
Lauren Greer
Lauren Greer is a notable individual recognized for achievements significant enough to be associated with the surname Greer.
-
E.
Lauren McCauley
Lauren McCauley is a character in the crime drama series "Black Bird," involved in the story surrounding the investigation and psychological dynamics of the case.
- F. None of above. chosen
Provenance (5 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59176b28819092384fc5f8968022 |
completed | April 27, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b4de30fb48190b2c0961e8f50f6c6 |
completed | May 18, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_6a0b50ca48648190806c5c4af619d1d6 |
completed | May 18, 2026, 5:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b515b7350819081c9f3a5103687eb |
completed | May 18, 2026, 5:50 p.m. |
Created at: April 16, 2026, 6:36 p.m.