Triple
T18933279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Courtney Gains |
E463170
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Gains
Gains is the surname of American character actor Courtney Gains, known for roles in films like "Children of the Corn" and "Back to the Future."
|
E1350150
|
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: Gains | Statement: [Courtney Gains, familyName, Gains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gains Context triple: [Courtney Gains, familyName, Gains]
-
A.
Gain
Gain is a popular Procter & Gamble laundry detergent brand known for its strong, long-lasting fragrances.
-
B.
Gaini
The Gaini were an Anglo-Saxon noble kin-group or tribe associated with Mercian aristocracy in early medieval England.
-
C.
Winning
"Winning" is a popular rock song by Santana, known for its uplifting lyrics and melodic guitar-driven sound.
-
D.
Winning
Winning is a 1969 American sports drama film starring Paul Newman as a race car driver whose obsession with success strains his personal relationships.
-
E.
Winning
"Winning" is a bestselling management and leadership book by former General Electric CEO Jack Welch that offers practical advice on business strategy, people management, and corporate success.
- 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: Gains Triple: [Courtney Gains, familyName, Gains]
Generated description
Gains is the surname of American character actor Courtney Gains, known for roles in films like "Children of the Corn" and "Back to the Future."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gains Target entity description: Gains is the surname of American character actor Courtney Gains, known for roles in films like "Children of the Corn" and "Back to the Future."
-
A.
Gain
Gain is a popular Procter & Gamble laundry detergent brand known for its strong, long-lasting fragrances.
-
B.
Gaini
The Gaini were an Anglo-Saxon noble kin-group or tribe associated with Mercian aristocracy in early medieval England.
-
C.
Winning
"Winning" is a popular rock song by Santana, known for its uplifting lyrics and melodic guitar-driven sound.
-
D.
Winning
Winning is a 1969 American sports drama film starring Paul Newman as a race car driver whose obsession with success strains his personal relationships.
-
E.
Winning
"Winning" is a bestselling management and leadership book by former General Electric CEO Jack Welch that offers practical advice on business strategy, people management, and corporate success.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3e498308190bd1594cca841199c |
completed | April 20, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a059122dff081909fb907b752a2934f |
completed | May 14, 2026, 9:08 a.m. |
| NEDg | Description generation | batch_6a0595f0ebd08190bcaa378ca15ae40f |
completed | May 14, 2026, 9:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05969a874c81909a1392c4268bad75 |
completed | May 14, 2026, 9:32 a.m. |
Created at: April 10, 2026, 11:59 a.m.