Triple
T10587983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marr |
E249903
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Alison Marr
Alison Marr is a mathematician known for her work in combinatorics and for her contributions to mathematics education and outreach.
|
E949509
|
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: Alison Marr | Statement: [Marr, hasNotableBearer, Alison Marr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alison Marr Context triple: [Marr, hasNotableBearer, Alison Marr]
-
A.
Alison Porter
Alison Porter is a central character in John Osborne’s play "Look Back in Anger," portrayed as the emotionally conflicted and long-suffering wife of the protagonist, Jimmy Porter.
-
B.
Alison Benson
Alison Benson is a television producer and executive known for her work overseeing series such as the comedy show "Camping."
-
C.
Alison Reid
Alison Reid is an actress known for her role in the period drama film "Esther Kahn."
-
D.
Alison Woods
Alison Woods is an American actress best known for her role in the horror-comedy film "Detention."
-
E.
Alison Owen
Alison Owen is a British film producer known for acclaimed works such as "Elizabeth," "Shaun of the Dead," and "Saving Mr. Banks."
- 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: Alison Marr Triple: [Marr, hasNotableBearer, Alison Marr]
Generated description
Alison Marr is a mathematician known for her work in combinatorics and for her contributions to mathematics education and outreach.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alison Marr Target entity description: Alison Marr is a mathematician known for her work in combinatorics and for her contributions to mathematics education and outreach.
-
A.
Alison Porter
Alison Porter is a central character in John Osborne’s play "Look Back in Anger," portrayed as the emotionally conflicted and long-suffering wife of the protagonist, Jimmy Porter.
-
B.
Alison Benson
Alison Benson is a television producer and executive known for her work overseeing series such as the comedy show "Camping."
-
C.
Alison Reid
Alison Reid is an actress known for her role in the period drama film "Esther Kahn."
-
D.
Alison Woods
Alison Woods is an American actress best known for her role in the horror-comedy film "Detention."
-
E.
Alison Owen
Alison Owen is a British film producer known for acclaimed works such as "Elizabeth," "Shaun of the Dead," and "Saving Mr. Banks."
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d527793c588190bfe3a5261eb7f919 |
completed | April 7, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f1658e03a8819098ea2ac2f818a61a |
completed | April 29, 2026, 1:57 a.m. |
| NEDg | Description generation | batch_69f16e31ebfc81908255e24b96bf9a99 |
completed | April 29, 2026, 2:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f1a09eae7481908200709ae9721d53 |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 6, 2026, 12:40 p.m.