Triple
T9211076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Mulligan |
E221117
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Mulligan
Mulligan is a surname of Irish origin commonly borne by individuals of Irish descent, including various notable figures in entertainment and sports.
|
E67931
|
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: Mulligan | Statement: [Richard Mulligan, familyName, Mulligan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mulligan Context triple: [Richard Mulligan, familyName, Mulligan]
-
A.
Mullett
Mullett is a surname most notably associated with Alfred B. Mullett, a 19th-century American architect known for designing prominent federal buildings.
-
B.
Murphy
Murphy is a residential suburb located within the Dallas metropolitan area in Texas.
-
C.
Murphy
Murphy is a common Irish-origin surname borne by numerous notable individuals across entertainment, politics, sports, and other fields.
-
D.
The Mister
The Mister is a contemporary romance novel by E. L. James, known for its Cinderella-style love story and for being her follow-up to the Fifty Shades series.
-
E.
Mullaney
Mullaney is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
- 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: Mulligan Triple: [Richard Mulligan, familyName, Mulligan]
Generated description
Mulligan is a surname of Irish origin commonly borne by individuals of Irish descent, including various notable figures in entertainment and sports.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mulligan Target entity description: Mulligan is a surname of Irish origin commonly borne by individuals of Irish descent, including various notable figures in entertainment and sports.
-
A.
Mullett
Mullett is a surname most notably associated with Alfred B. Mullett, a 19th-century American architect known for designing prominent federal buildings.
-
B.
Murphy
Murphy is a residential suburb located within the Dallas metropolitan area in Texas.
-
C.
Murphy
chosen
Murphy is a common Irish-origin surname borne by numerous notable individuals across entertainment, politics, sports, and other fields.
-
D.
The Mister
The Mister is a contemporary romance novel by E. L. James, known for its Cinderella-style love story and for being her follow-up to the Fifty Shades series.
-
E.
Mullaney
Mullaney is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
- F. None of above.
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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b54520819087030148dadd6385 |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065efcb64819097d4624bd9e423d2 |
completed | April 4, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_69d06770ccf08190b00bf35c16a80071 |
completed | April 4, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d06864b8c48190b8e08ab9c1c85c9a |
completed | April 4, 2026, 1:24 a.m. |
Created at: March 30, 2026, 7:27 p.m.