Triple
T5356134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Siegel |
E102695
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object |
Madigan
Madigan is a 1968 American crime drama film starring Richard Widmark as a tough New York City police detective navigating corruption and moral ambiguity.
|
E514174
|
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: Madigan | Statement: [Don Siegel, directed, Madigan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madigan Context triple: [Don Siegel, directed, Madigan]
-
A.
Corrigan
Corrigan is an Irish-origin surname borne by numerous notable figures in fields such as religion, politics, sports, and entertainment.
-
B.
Govandi
Govandi is a densely populated neighborhood in eastern Mumbai known for its informal settlements, industrial areas, and proximity to major transport routes.
-
C.
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.
-
D.
McDermid
McDermid is a Scottish surname, often a variant of McDiarmid, borne by various individuals of Scottish and Irish heritage.
-
E.
Millard
Millard is the given name of Millard Fillmore, the 13th president of the United States.
- 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: Madigan Triple: [Don Siegel, directed, Madigan]
Generated description
Madigan is a 1968 American crime drama film starring Richard Widmark as a tough New York City police detective navigating corruption and moral ambiguity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Madigan Target entity description: Madigan is a 1968 American crime drama film starring Richard Widmark as a tough New York City police detective navigating corruption and moral ambiguity.
-
A.
Corrigan
Corrigan is an Irish-origin surname borne by numerous notable figures in fields such as religion, politics, sports, and entertainment.
-
B.
Govandi
Govandi is a densely populated neighborhood in eastern Mumbai known for its informal settlements, industrial areas, and proximity to major transport routes.
-
C.
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.
-
D.
McDermid
McDermid is a Scottish surname, often a variant of McDiarmid, borne by various individuals of Scottish and Irish heritage.
-
E.
Millard
Millard is the given name of Millard Fillmore, the 13th president of the United States.
- 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_69bd43d8f7248190b64c140734b5c9a8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd862f0ea48190bec78690ab3bee51 |
completed | March 20, 2026, 5:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21e2b7b08190aca4c2855ff041de |
completed | March 21, 2026, 10:55 p.m. |
| NEDg | Description generation | batch_69bf228956d481909e9f3c11f4597cce |
completed | March 21, 2026, 10:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf230b571481909f76ada72d94c8d8 |
completed | March 21, 2026, 11 p.m. |
Created at: March 20, 2026, 2:01 p.m.