Triple
T14488237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thunder |
E359292
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Maureen McDonald
Maureen McDonald is a writer best known for her work on the animated television series "Thunder."
|
E1357643
|
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: Maureen McDonald | Statement: [Thunder, writer, Maureen McDonald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maureen McDonald Context triple: [Thunder, writer, Maureen McDonald]
-
A.
Marilyn McLeod
Marilyn McLeod was an American songwriter best known for co-writing several Motown hits, including Diana Ross’s disco classic “Love Hangover.”
-
B.
Maureen Nolan
Maureen Nolan is an Irish-born English singer and actress best known as a member of the pop group The Nolans.
-
C.
Maureen Garrett
Maureen Garrett is an American actress best known for her long-running role as Holly Norris on the soap opera "Guiding Light."
-
D.
Maureen Earl
Maureen Earl is best known as the wife of American novelist Clifford Irving, who gained notoriety for his fraudulent "autobiography" of Howard Hughes.
-
E.
Maureen Sweeney
Maureen Sweeney is an Irish woman best known for her crucial World War II weather observations that influenced the timing of the D-Day landings.
- 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: Maureen McDonald Triple: [Thunder, writer, Maureen McDonald]
Generated description
Maureen McDonald is a writer best known for her work on the animated television series "Thunder."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maureen McDonald Target entity description: Maureen McDonald is a writer best known for her work on the animated television series "Thunder."
-
A.
Marilyn McLeod
Marilyn McLeod was an American songwriter best known for co-writing several Motown hits, including Diana Ross’s disco classic “Love Hangover.”
-
B.
Maureen Nolan
Maureen Nolan is an Irish-born English singer and actress best known as a member of the pop group The Nolans.
-
C.
Maureen Garrett
Maureen Garrett is an American actress best known for her long-running role as Holly Norris on the soap opera "Guiding Light."
-
D.
Maureen Earl
Maureen Earl is best known as the wife of American novelist Clifford Irving, who gained notoriety for his fraudulent "autobiography" of Howard Hughes.
-
E.
Maureen Sweeney
Maureen Sweeney is an Irish woman best known for her crucial World War II weather observations that influenced the timing of the D-Day landings.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930bd1d48190abd6c47da0a3ebc8 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05dd78297481909812d1e38d946a87 |
completed | May 14, 2026, 2:34 p.m. |
| NEDg | Description generation | batch_6a05dfcd85b08190b0ec431590396dbb |
completed | May 14, 2026, 2:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05e09c58308190975c69c86482292a |
completed | May 14, 2026, 2:47 p.m. |
Created at: April 10, 2026, 1:20 a.m.