Triple
T20093019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernard Gersten |
E496321
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Laura Ross
Laura Ross is the daughter of prominent American theater producer and administrator Bernard Gersten.
|
E1512438
|
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: Laura Ross | Statement: [Bernard Gersten, hasChild, Laura Ross]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Ross Context triple: [Bernard Gersten, hasChild, Laura Ross]
-
A.
Melissa Ross
Melissa Ross is a television producer known for her work on the home design and lifestyle program "Ideal Home."
-
B.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
C.
Laura Malinger
Laura Malinger is the mother of American former child actor Ross Malinger, known for his role in the film "Sleepless in Seattle."
-
D.
Lori Ross
Lori Ross is a character in the crime drama miniseries "Mare of Easttown," known as Mare Sheehan’s close friend whose family becomes entangled in the central mystery.
-
E.
Mary Beth Johnson
Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
- 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: Laura Ross Triple: [Bernard Gersten, hasChild, Laura Ross]
Generated description
Laura Ross is the daughter of prominent American theater producer and administrator Bernard Gersten.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laura Ross Target entity description: Laura Ross is the daughter of prominent American theater producer and administrator Bernard Gersten.
-
A.
Melissa Ross
Melissa Ross is a television producer known for her work on the home design and lifestyle program "Ideal Home."
-
B.
Mary Beth Hughes
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
-
C.
Laura Malinger
Laura Malinger is the mother of American former child actor Ross Malinger, known for his role in the film "Sleepless in Seattle."
-
D.
Lori Ross
Lori Ross is a character in the crime drama miniseries "Mare of Easttown," known as Mare Sheehan’s close friend whose family becomes entangled in the central mystery.
-
E.
Mary Beth Johnson
Mary Beth Johnson is known as the wife of American Western film actor Charles Starrett.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66668db8881908c43b1deef9af1d3 |
completed | April 20, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a6d6015e081909fea513c07e31ac4 |
completed | May 18, 2026, 1:37 a.m. |
| NEDg | Description generation | batch_6a0a6ebd63888190a21c3d4907b5c38a |
completed | May 18, 2026, 1:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a6f3de2e88190824c9cc266c7ee8c |
completed | May 18, 2026, 1:45 a.m. |
Created at: April 11, 2026, 11:22 p.m.