Triple
T9731546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothy Malone |
E235754
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Maloney
Maloney is a surname most notably associated with American actress Dorothy Malone, known for her roles in classic Hollywood films and television.
|
E817161
|
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: Maloney | Statement: [Dorothy Malone, familyName, Maloney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maloney Context triple: [Dorothy Malone, familyName, Maloney]
-
A.
Mullaney
Mullaney is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
-
B.
Malone
Malone is a common English-language surname borne by numerous notable individuals across sports, entertainment, and public life.
-
C.
Mahony
Mahony is the surname of Marion Mahony Griffin, a pioneering American architect and one of the first licensed female architects in the world.
-
D.
Mulally
Mulally is the surname of Alan Mulally, the American engineer and former CEO known for leading major turnarounds at Boeing and Ford Motor Company.
-
E.
Murphy
Murphy is a residential suburb located within the Dallas metropolitan area in Texas.
- 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: Maloney Triple: [Dorothy Malone, familyName, Maloney]
Generated description
Maloney is a surname most notably associated with American actress Dorothy Malone, known for her roles in classic Hollywood films and television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maloney Target entity description: Maloney is a surname most notably associated with American actress Dorothy Malone, known for her roles in classic Hollywood films and television.
-
A.
Mullaney
Mullaney is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
-
B.
Malone
Malone is a common English-language surname borne by numerous notable individuals across sports, entertainment, and public life.
-
C.
Mahony
Mahony is the surname of Marion Mahony Griffin, a pioneering American architect and one of the first licensed female architects in the world.
-
D.
Mulally
Mulally is the surname of Alan Mulally, the American engineer and former CEO known for leading major turnarounds at Boeing and Ford Motor Company.
-
E.
Murphy
Murphy is a residential suburb located within the Dallas metropolitan area in Texas.
- 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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eb2373c81909139c7a2ff2aa541 |
completed | April 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19fb97b6c81908d5f1d4f587a9188 |
completed | April 4, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69d1a16fa29c8190be50ddaa566fcd7f |
completed | April 4, 2026, 11:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1a335f2808190aca0c1689787b90a |
completed | April 4, 2026, 11:48 p.m. |
Created at: March 30, 2026, 8:22 p.m.