Triple
T10444589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Nolan |
E246253
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object |
Michael Nolan
Michael Nolan is an individual known primarily in relation to Sarah Nolan as a family member sharing the Nolan surname.
|
E887875
|
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: Michael Nolan | Statement: [Sarah Nolan, relative, Michael Nolan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Nolan Context triple: [Sarah Nolan, relative, Michael Nolan]
-
A.
Kevin Nolan
Kevin Nolan is an English former professional footballer best known as a goal-scoring midfielder for clubs such as Bolton Wanderers, Newcastle United, and West Ham United.
-
B.
Joseph Nolan
Joseph Nolan is the father of British-American novelist and filmmaker Christopher Nolan.
-
C.
David Nolan
David Nolan is a relatively common personal name shared by multiple individuals, including politicians, athletes, and fictional characters.
-
D.
Ian Donnelly
Ian Donnelly is a theoretical physicist and linguist who serves as one of the central human protagonists in the science fiction film "Arrival," working alongside Louise Banks to communicate with extraterrestrial visitors.
-
E.
Chris Donlon
Chris Donlon is a film editor known for his work on the feature film "Kicks."
- 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: Michael Nolan Triple: [Sarah Nolan, relative, Michael Nolan]
Generated description
Michael Nolan is an individual known primarily in relation to Sarah Nolan as a family member sharing the Nolan surname.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Nolan Target entity description: Michael Nolan is an individual known primarily in relation to Sarah Nolan as a family member sharing the Nolan surname.
-
A.
Kevin Nolan
Kevin Nolan is an English former professional footballer best known as a goal-scoring midfielder for clubs such as Bolton Wanderers, Newcastle United, and West Ham United.
-
B.
Joseph Nolan
Joseph Nolan is the father of British-American novelist and filmmaker Christopher Nolan.
-
C.
David Nolan
David Nolan is a relatively common personal name shared by multiple individuals, including politicians, athletes, and fictional characters.
-
D.
Ian Donnelly
Ian Donnelly is a theoretical physicist and linguist who serves as one of the central human protagonists in the science fiction film "Arrival," working alongside Louise Banks to communicate with extraterrestrial visitors.
-
E.
Chris Donlon
Chris Donlon is a film editor known for his work on the feature film "Kicks."
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdbe5dc48190b4291bfd0fb988eb |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de8413f30c8190aebe1504e213b6cc |
completed | April 14, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69de8e6f3fac8190bcd1675978d6d6d7 |
completed | April 14, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de8fa679cc81909cb51035e5403ce9 |
completed | April 14, 2026, 7:04 p.m. |
Created at: April 6, 2026, 12:16 p.m.